In [1]:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.model_selection import train_test_split, KFold, cross_val_score
seed = 10
num_folds=10
from sklearn import metrics
from sklearn.linear_model import LinearRegression, Ridge, Lasso
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import mean_squared_error,r2_score
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import AdaBoostRegressor, GradientBoostingRegressor, RandomForestRegressor, ExtraTreesRegressor
from sklearn.neighbors import KNeighborsRegressor
from sklearn.metrics import silhouette_score, mean_absolute_error
from sklearn.metrics import pairwise_distances
from sklearn.model_selection import GridSearchCV
from sklearn.svm import SVR
from statsmodels.api import OLS
In [2]:
# Importing the data set
data = pd.read_csv('concrete.csv')
data.head()
Out[2]:
| cement | slag | ash | water | superplastic | coarseagg | fineagg | age | strength | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 971.8 | 748.5 | 28 | 29.89 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 10.8 | 1080.8 | 796.2 | 14 | 23.51 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 5.5 | 956.9 | 861.2 | 28 | 29.22 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 0.0 | 932.0 | 670.0 | 28 | 45.85 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 9.1 | 1047.4 | 696.7 | 28 | 18.29 |
In [3]:
# meanings of independent variables:
# 0) cement: amount of cement added to the concrete in kg/m3
# 1) slag: is a component mixed with cement to increase it strength and resistance to chemical attacks
# 2) fly ash : it is another component added with cement to increase its properties
# 3) water: is also another component that is added with cement for hardening
# 4) superplastic: it is added with cement to control the compressive strength
# 5) coarseagg: these are larger particles that are added to the concrete to reduce shrinkage. For eg: granules
# 6) fineagg: finen aggregates are components that are added aling with coarse aggregate to tackle shrinkage and reduce the overall
# amount of cement needed
# 7) age: It is the number of days they left the concrete to dry out, before the strength was measured
Performing EDA¶
In [4]:
data.shape
Out[4]:
(1030, 9)
In [5]:
data.dtypes
# All the data are of float except for 'age', which is of integer type
Out[5]:
cement float64 slag float64 ash float64 water float64 superplastic float64 coarseagg float64 fineagg float64 age int64 strength float64 dtype: object
In [6]:
data.isnull().sum()
# no NAN entries
Out[6]:
cement 0 slag 0 ash 0 water 0 superplastic 0 coarseagg 0 fineagg 0 age 0 strength 0 dtype: int64
In [7]:
print("The number of null entries in: \n")
for i in data.columns:
print("{} : {}".format(i,(data[i]==0).sum()))
# Although there are no null entries, the number of '0' entries is a lot. However, these 0's cannot be considered as null entries
# because it is possible that the amount of slag, super plastic and fly ash 'added' might actually be 'zero'
# Therefore NO ACTION is taken against these 'zero values'
The number of null entries in: cement : 0 slag : 471 ash : 566 water : 0 superplastic : 379 coarseagg : 0 fineagg : 0 age : 0 strength : 0
In [8]:
for i in data.columns:
print("The Q1 of {} is {:.3f} \nThe Q2 of {} is {:.3f} \nThe Q3 of {} is {:.3f}\n".format(i,np.percentile(data[i],25),i,np.percentile(data[i],50),i,np.percentile(data[i],75)))
The Q1 of cement is 192.375 The Q2 of cement is 272.900 The Q3 of cement is 350.000 The Q1 of slag is 0.000 The Q2 of slag is 22.000 The Q3 of slag is 142.950 The Q1 of ash is 0.000 The Q2 of ash is 0.000 The Q3 of ash is 118.300 The Q1 of water is 164.900 The Q2 of water is 185.000 The Q3 of water is 192.000 The Q1 of superplastic is 0.000 The Q2 of superplastic is 6.400 The Q3 of superplastic is 10.200 The Q1 of coarseagg is 932.000 The Q2 of coarseagg is 968.000 The Q3 of coarseagg is 1029.400 The Q1 of fineagg is 730.950 The Q2 of fineagg is 779.500 The Q3 of fineagg is 824.000 The Q1 of age is 7.000 The Q2 of age is 28.000 The Q3 of age is 56.000 The Q1 of strength is 23.710 The Q2 of strength is 34.445 The Q3 of strength is 46.135
In [9]:
data.skew()
# Superplastic and slag seems to be somewhat skewed.
# Age is highly skewed.
# Let's check about this more in the univariate analysis
Out[9]:
cement 0.509481 slag 0.800717 ash 0.537354 water 0.074628 superplastic 0.907203 coarseagg -0.040220 fineagg -0.253010 age 3.269177 strength 0.416977 dtype: float64
In [10]:
plt.figure(figsize=(20,10))
plt.subplot(2,4,1)
plt.hist(data['cement'],color='green',bins=80)
plt.xlabel('cement')
plt.subplot(2,4,2)
plt.hist(data['slag'],color='orange')
plt.xlabel('slag')
plt.subplot(2,4,3)
plt.hist(data['ash'],color='brown',bins=80)
plt.xlabel('ash')
plt.subplot(2,4,4)
plt.hist(data['water'],color='green',bins=80)
plt.xlabel('water')
plt.show()
# cement and water are somewhat normally distributed
# slag and ash are highly skewed toward the right, this is due to the fact that many of it's values are '0'
In [11]:
plt.figure(figsize=(20,10))
plt.subplot(2,4,1)
plt.hist(data['superplastic'],color='green',bins=80)
plt.xlabel('superplastic')
plt.subplot(2,4,2)
plt.hist(data['coarseagg'],color='orange')
plt.xlabel('coarseagg')
plt.subplot(2,4,3)
plt.hist(data['fineagg'],color='brown',bins=80)
plt.xlabel('fineagg')
plt.subplot(2,4,4)
plt.hist(data['age'],color='green',bins=80)
plt.xlabel('age')
plt.show()
# superplastic and age is highly skewed to the right
# coarseagg and fineagg is normally distributed
In [12]:
plt.figure(figsize=(15,5))
plt.subplot(1,2,1)
plt.hist(data['strength'],color='black',bins=75)
plt.subplot(1,2,2)
sns.kdeplot(data['strength'],color='red',shade=True)
plt.show()
# strength seems to be normally distributed
In [13]:
data_eda = data.copy()
In [14]:
for i in range(0,len(data_eda['age'])):
if data_eda['age'][i]<=50:
data_eda['age'][i]='Below 50'
elif ((data_eda['age'][i]>50) & (data_eda['age'][i]<=100)):
data_eda['age'][i]='50-100'
elif ((data_eda['age'][i]>100) & (data_eda['age'][i]<=150)):
data_eda['age'][i]='100-150'
elif ((data_eda['age'][i]>150) & (data_eda['age'][i]<=200)):
data_eda['age'][i]='150-200'
elif ((data_eda['age'][i]>200) & (data_eda['age'][i]<=250)):
data_eda['age'][i]='200-250'
elif ((data_eda['age'][i]>250) & (data_eda['age'][i]<=300)):
data_eda['age'][i]='250-300'
elif ((data_eda['age'][i]>300) & (data_eda['age'][i]<=350)):
data_eda['age'][i]='300-350'
elif ((data_eda['age'][i]>350) & (data_eda['age'][i]<=400)):
data_eda['age'][i]='350-400'
D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:3: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy This is separate from the ipykernel package so we can avoid doing imports until D:\Apps\bandi\lib\site-packages\pandas\core\indexing.py:670: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self._setitem_with_indexer(indexer, value) D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:5: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy """ D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:9: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy if __name__ == '__main__': D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:17: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:13: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy del sys.path[0] D:\Apps\bandi\lib\site-packages\ipykernel_launcher.py:7: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy import sys
In [15]:
sns.countplot(data_eda['age'], order=['Below 50','50-100','100-150','150-200','200-250','250-300','300-350','350-400'])
plt.show()
# most of the concrete's strength are measured within less than '50 days'
In [16]:
data.describe().T
# The mean of slag is 73,and 3rd quartile is 142. however the max value is 359
# The mean of ash is 54,and 3rd quartile is 118. however the max value is 200
# The mean of superplastic is 6,and 3rd quartile is 10. however the max value is 32
# The mean of age is 45,and 3rd quartile is 56. however the max value is 365
# "which means there is presence of outliers"
Out[16]:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| cement | 1030.0 | 281.167864 | 104.506364 | 102.00 | 192.375 | 272.900 | 350.000 | 540.0 |
| slag | 1030.0 | 73.895825 | 86.279342 | 0.00 | 0.000 | 22.000 | 142.950 | 359.4 |
| ash | 1030.0 | 54.188350 | 63.997004 | 0.00 | 0.000 | 0.000 | 118.300 | 200.1 |
| water | 1030.0 | 181.567282 | 21.354219 | 121.80 | 164.900 | 185.000 | 192.000 | 247.0 |
| superplastic | 1030.0 | 6.204660 | 5.973841 | 0.00 | 0.000 | 6.400 | 10.200 | 32.2 |
| coarseagg | 1030.0 | 972.918932 | 77.753954 | 801.00 | 932.000 | 968.000 | 1029.400 | 1145.0 |
| fineagg | 1030.0 | 773.580485 | 80.175980 | 594.00 | 730.950 | 779.500 | 824.000 | 992.6 |
| age | 1030.0 | 45.662136 | 63.169912 | 1.00 | 7.000 | 28.000 | 56.000 | 365.0 |
| strength | 1030.0 | 35.817961 | 16.705742 | 2.33 | 23.710 | 34.445 | 46.135 | 82.6 |
In [17]:
data.std()
Out[17]:
cement 104.506364 slag 86.279342 ash 63.997004 water 21.354219 superplastic 5.973841 coarseagg 77.753954 fineagg 80.175980 age 63.169912 strength 16.705742 dtype: float64
In [18]:
for i in data.columns:
print("The mean and median of {} is {:.3f} & {} respectively\n".format(i,data[i].mean(),data[i].median()))
The mean and median of cement is 281.168 & 272.9 respectively The mean and median of slag is 73.896 & 22.0 respectively The mean and median of ash is 54.188 & 0.0 respectively The mean and median of water is 181.567 & 185.0 respectively The mean and median of superplastic is 6.205 & 6.4 respectively The mean and median of coarseagg is 972.919 & 968.0 respectively The mean and median of fineagg is 773.580 & 779.5 respectively The mean and median of age is 45.662 & 28.0 respectively The mean and median of strength is 35.818 & 34.445 respectively
In [19]:
data.corr()
# None of the independent attributes are highly correlated. Which is good news
# However, there are to attributes which are in "high" correlation with "strength" too
Out[19]:
| cement | slag | ash | water | superplastic | coarseagg | fineagg | age | strength | |
|---|---|---|---|---|---|---|---|---|---|
| cement | 1.000000 | -0.275216 | -0.397467 | -0.081587 | 0.092386 | -0.109349 | -0.222718 | 0.081946 | 0.497832 |
| slag | -0.275216 | 1.000000 | -0.323580 | 0.107252 | 0.043270 | -0.283999 | -0.281603 | -0.044246 | 0.134829 |
| ash | -0.397467 | -0.323580 | 1.000000 | -0.256984 | 0.377503 | -0.009961 | 0.079108 | -0.154371 | -0.105755 |
| water | -0.081587 | 0.107252 | -0.256984 | 1.000000 | -0.657533 | -0.182294 | -0.450661 | 0.277618 | -0.289633 |
| superplastic | 0.092386 | 0.043270 | 0.377503 | -0.657533 | 1.000000 | -0.265999 | 0.222691 | -0.192700 | 0.366079 |
| coarseagg | -0.109349 | -0.283999 | -0.009961 | -0.182294 | -0.265999 | 1.000000 | -0.178481 | -0.003016 | -0.164935 |
| fineagg | -0.222718 | -0.281603 | 0.079108 | -0.450661 | 0.222691 | -0.178481 | 1.000000 | -0.156095 | -0.167241 |
| age | 0.081946 | -0.044246 | -0.154371 | 0.277618 | -0.192700 | -0.003016 | -0.156095 | 1.000000 | 0.328873 |
| strength | 0.497832 | 0.134829 | -0.105755 | -0.289633 | 0.366079 | -0.164935 | -0.167241 | 0.328873 | 1.000000 |
In [20]:
plt.figure(figsize=(15,10))
sns.heatmap(data.corr(),annot=True)
plt.show()
# no high correlated attributes
# The highest correlated attribute with 'strength' is 'cement' with a correlation of 0.50
# The second highest would be 'superplastic' with 0.37, followed by 'age' (0.33) and 'water' (0.29)
# Among the independent attributes, 'water' & 'superplastic' seem to be of (0.66), negative correlation
# 'fine agg' and 'water' seem to be negatively correlated (0.45)
In [21]:
plt.figure(figsize=(10,8))
sns.boxplot(data=data,orient="h")
plt.show()
# Outliers are present in slag, water, superplastic, fineagg, age,strength.
In [22]:
sns.pairplot(data,diag_kind='kde')
plt.show()
# From the scattered points from the below pair-plot, it is kind of clear that all the attributes are not so correlated at all.
# Amongst everything the highly correlated is cement & strength (0.5)
# Also there could be 3 - 15 clusters (there are 3 to 5 gaussians, as observed from the "diag_kde plot")
# Since there are no highly correlated attributes, i am concluding that all the attributes are to be kept for analysis
In [23]:
sns.jointplot('cement','strength',data=data,color='green',kind='reg')
plt.show()
# From the below scatter plot, It is clear that, "if more amount of cement is added, the strength is higher"
# In other words, compressive strength of concrete increases with increase in the amount of cement
Treatment of Outliers¶
In [24]:
Q1 = data.quantile(0.25)
Q3 = data.quantile(0.75)
IQR = Q3-Q1
In [25]:
data[((data < (Q1-1.5*IQR)) | (data>(Q3+1.5*IQR))).any(axis=1)]
# There are only 89 rows of outliers.
# It is better to remove them off rather than corrupt the data with imputing the outliers with median values
Out[25]:
| cement | slag | ash | water | superplastic | coarseagg | fineagg | age | strength | |
|---|---|---|---|---|---|---|---|---|---|
| 44 | 531.3 | 0.0 | 0.0 | 141.8 | 28.2 | 852.1 | 893.7 | 91 | 59.20 |
| 51 | 331.0 | 0.0 | 0.0 | 192.0 | 0.0 | 978.0 | 825.0 | 180 | 39.00 |
| 64 | 332.5 | 142.5 | 0.0 | 228.0 | 0.0 | 932.0 | 594.0 | 365 | 41.05 |
| 66 | 237.0 | 92.0 | 71.0 | 247.0 | 6.0 | 853.0 | 695.0 | 28 | 28.63 |
| 93 | 427.5 | 47.5 | 0.0 | 228.0 | 0.0 | 932.0 | 594.0 | 180 | 41.84 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 995 | 380.0 | 0.0 | 0.0 | 228.0 | 0.0 | 932.0 | 670.0 | 365 | 52.52 |
| 1003 | 323.7 | 282.8 | 0.0 | 183.8 | 10.3 | 942.7 | 659.9 | 56 | 80.20 |
| 1017 | 139.6 | 209.4 | 0.0 | 192.0 | 0.0 | 1047.0 | 806.9 | 180 | 44.21 |
| 1026 | 531.3 | 0.0 | 0.0 | 141.8 | 28.2 | 852.1 | 893.7 | 3 | 41.30 |
| 1028 | 342.0 | 38.0 | 0.0 | 228.0 | 0.0 | 932.0 | 670.0 | 270 | 55.06 |
89 rows × 9 columns
In [26]:
cleandf = data[~((data < (Q1 - 1.5 * IQR)) | (data > (Q3 + 1.5 * IQR))).any(axis=1)]
cleandf.shape
# removing off the values from data which are lesser than "1.5 times the IQR" from "1st quartile" and
# greater than "1.5 times IQR" from the "3rd quartile"
# which removes off 89 rows.
Out[26]:
(941, 9)
In [27]:
plt.figure(figsize=(10,8))
sns.boxplot(data=cleandf,orient="h")
plt.show()
# The cleaned data and is free of old outliers.
# However, new outliers are formed
In [28]:
cleandf.describe().T
# Now there is no significant difference between the 75% value and "max" value, as when observed without removing outliers
Out[28]:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| cement | 941.0 | 275.765250 | 101.888133 | 102.00 | 190.30 | 255.5 | 349.00 | 540.0 |
| slag | 941.0 | 73.860680 | 86.357928 | 0.00 | 0.00 | 20.0 | 145.00 | 342.1 |
| ash | 941.0 | 58.019979 | 64.363959 | 0.00 | 0.00 | 0.0 | 118.30 | 200.1 |
| water | 941.0 | 180.618066 | 18.748963 | 127.00 | 164.90 | 183.8 | 192.00 | 228.0 |
| superplastic | 941.0 | 6.247396 | 5.340911 | 0.00 | 0.00 | 7.0 | 10.30 | 22.1 |
| coarseagg | 941.0 | 974.808289 | 77.646578 | 801.00 | 932.00 | 968.0 | 1031.00 | 1145.0 |
| fineagg | 941.0 | 776.551860 | 75.075034 | 594.00 | 741.00 | 780.0 | 822.20 | 945.0 |
| age | 941.0 | 32.376196 | 28.558690 | 1.00 | 7.00 | 28.0 | 28.00 | 120.0 |
| strength | 941.0 | 34.887641 | 16.592538 | 2.33 | 22.63 | 33.4 | 44.64 | 79.4 |
In [29]:
data_fin = cleandf.copy()
data_fin.head()
Out[29]:
| cement | slag | ash | water | superplastic | coarseagg | fineagg | age | strength | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 971.8 | 748.5 | 28 | 29.89 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 10.8 | 1080.8 | 796.2 | 14 | 23.51 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 5.5 | 956.9 | 861.2 | 28 | 29.22 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 0.0 | 932.0 | 670.0 | 28 | 45.85 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 9.1 | 1047.4 | 696.7 | 28 | 18.29 |
In [30]:
data_fin['coarseagg_perkg_of_fineagg'] = data['coarseagg']/data['fineagg']
# since coarse_agg and fine_agg are mixed as an additional compound to fill in the air gaps,
# we can create a composite data, which is a combination of coarseagg and finagg
# It means that, the amount of coarsgeagg added "per kg" of fineagg
In [31]:
data = data_fin.copy()
data = data.drop({'coarseagg','fineagg'},axis=1)
In [32]:
z = data['strength']
data = data.drop('strength',axis=1)
data['strength']=z
In [33]:
data = data.reset_index()
data.drop({'index'},inplace=True,axis=1)
data.head()
Out[33]:
| cement | slag | ash | water | superplastic | age | coarseagg_perkg_of_fineagg | strength | |
|---|---|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 28 | 1.298330 | 29.89 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 10.8 | 14 | 1.357448 | 23.51 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 5.5 | 28 | 1.111124 | 29.22 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 0.0 | 28 | 1.391045 | 45.85 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 9.1 | 28 | 1.503373 | 18.29 |
In [34]:
# For the complexity of the model, a simple linear model would do.
In [35]:
ss1 = StandardScaler()
data_scaled = ss1.fit_transform(data)
In [36]:
from sklearn.cluster import KMeans
cluster_range = range(3,16)
cluster_errors = []
for num_clusters in cluster_range:
clusters = KMeans(num_clusters, n_init = 5,random_state=seed)
clusters.fit(data_scaled)
labels = clusters.labels_
centroids = clusters.cluster_centers_
cluster_errors.append( clusters.inertia_ )
clusters_df = pd.DataFrame( { "num_clusters":cluster_range, "cluster_errors": cluster_errors } )
clusters_df
# From the below data on interia it is clear that the amount of error reduces significantly from 3 to 8.
# However, after 8, the inertia is reducing in very small amounts.
# Hence, we can take the number of clusters to be 8
Out[36]:
| num_clusters | cluster_errors | |
|---|---|---|
| 0 | 3 | 4957.325685 |
| 1 | 4 | 4309.993113 |
| 2 | 5 | 3898.941009 |
| 3 | 6 | 3616.441448 |
| 4 | 7 | 3383.037800 |
| 5 | 8 | 3090.333023 |
| 6 | 9 | 2922.667031 |
| 7 | 10 | 2763.261379 |
| 8 | 11 | 2620.133352 |
| 9 | 12 | 2502.652659 |
| 10 | 13 | 2436.289391 |
| 11 | 14 | 2309.029695 |
| 12 | 15 | 2258.108558 |
In [37]:
plt.figure(figsize=(12,6))
plt.plot(clusters_df.num_clusters, clusters_df.cluster_errors, marker = "o" )
# from the below graph it can be seen that the 'arm' bend is around 8. Hence let us try with 8clusters
Out[37]:
[<matplotlib.lines.Line2D at 0x1ef79f08f88>]
In [38]:
cluster = KMeans( n_clusters = 8, random_state = seed )
cluster.fit(data_scaled)
Out[38]:
KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,
n_clusters=8, n_init=10, n_jobs=None, precompute_distances='auto',
random_state=10, tol=0.0001, verbose=0)
In [39]:
pd.DataFrame(cluster.cluster_centers_,columns=data.columns)
Out[39]:
| cement | slag | ash | water | superplastic | age | coarseagg_perkg_of_fineagg | strength | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1.827938 | -0.202363 | -0.849063 | -0.224333 | -0.357855 | -0.059225 | 2.808816 | 0.966718 |
| 1 | -0.570946 | -0.012127 | 0.937661 | 0.648861 | 0.226899 | -0.212674 | -0.272337 | -0.346929 |
| 2 | -0.791717 | 1.361714 | -0.888505 | 0.625995 | -0.730773 | -0.522656 | 0.180831 | -0.692073 |
| 3 | 1.032841 | 0.533465 | -0.547342 | -0.883020 | 0.956609 | 0.052397 | -0.607144 | 1.269804 |
| 4 | 0.595541 | -0.817042 | -0.836880 | 0.627287 | -1.099492 | -0.563003 | 0.162576 | -0.669755 |
| 5 | -0.404638 | -0.650872 | 1.138279 | -0.867262 | 0.781306 | -0.549316 | -0.063396 | -0.429759 |
| 6 | 0.010467 | 0.113028 | -0.827733 | 1.067291 | -1.081901 | 2.034887 | 0.004062 | 0.321848 |
| 7 | -0.551169 | -0.607974 | 1.035652 | -0.773296 | 0.431355 | 1.650946 | -0.009493 | 0.752859 |
In [40]:
prediction=cluster.predict(data_scaled)
data["GROUP"] = prediction
data
Out[40]:
| cement | slag | ash | water | superplastic | age | coarseagg_perkg_of_fineagg | strength | GROUP | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 28 | 1.298330 | 29.89 | 2 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 10.8 | 14 | 1.357448 | 23.51 | 5 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 5.5 | 28 | 1.111124 | 29.22 | 1 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 0.0 | 28 | 1.391045 | 45.85 | 2 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 9.1 | 28 | 1.503373 | 18.29 | 2 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 936 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 7 | 1.298330 | 10.39 | 2 |
| 937 | 297.2 | 0.0 | 117.5 | 174.8 | 9.5 | 3 | 1.357399 | 21.91 | 5 |
| 938 | 135.0 | 0.0 | 166.0 | 180.0 | 10.0 | 28 | 1.193789 | 13.29 | 5 |
| 939 | 276.4 | 116.0 | 90.3 | 179.6 | 8.9 | 28 | 1.132500 | 44.28 | 1 |
| 940 | 540.0 | 0.0 | 0.0 | 173.0 | 0.0 | 7 | 1.835237 | 52.61 | 0 |
941 rows × 9 columns
CLUSTER ANALYSIS¶
In [41]:
data.groupby("GROUP").mean()
# Group 0 has the highest cement level, and is higher strength as well
# Group 2 has low cemnt content and low strength also
# Let us see more in details about the clusters
Out[41]:
| cement | slag | ash | water | superplastic | age | coarseagg_perkg_of_fineagg | strength | |
|---|---|---|---|---|---|---|---|---|
| GROUP | ||||||||
| 0 | 461.911429 | 56.394286 | 3.400000 | 176.414286 | 4.337143 | 30.685714 | 1.769694 | 50.919429 |
| 1 | 217.623567 | 72.814013 | 118.339490 | 192.777070 | 7.458599 | 26.305732 | 1.220918 | 29.134268 |
| 2 | 195.141549 | 191.392958 | 0.862676 | 192.348592 | 2.346479 | 17.457746 | 1.301630 | 23.410493 |
| 3 | 380.943590 | 119.905128 | 22.809615 | 164.071154 | 11.353846 | 33.871795 | 1.161286 | 55.945705 |
| 4 | 336.411565 | 3.340136 | 4.183673 | 192.372789 | 0.378231 | 16.306122 | 1.298379 | 23.780612 |
| 5 | 234.559355 | 17.682581 | 131.245161 | 164.366452 | 10.418065 | 16.696774 | 1.258132 | 27.760645 |
| 6 | 276.831148 | 83.616393 | 4.772131 | 200.618033 | 0.472131 | 90.459016 | 1.270146 | 40.225082 |
| 7 | 219.637500 | 21.385227 | 124.643182 | 166.127273 | 8.550000 | 79.500000 | 1.267732 | 47.372841 |
In [42]:
data.boxplot(by = 'GROUP', layout=(4,4), figsize=(20, 20))
plt.show()
In [43]:
X = pairwise_distances(data.iloc[:,0:-1])
metrics.silhouette_score(X,cluster.labels_)
# The value is very close to '0' which means that there are over-lapping clusters.
# However, since the silhouette score isn't negative, we can get releived of the fact that there are no points that a classified
# under the wrong group
Out[43]:
0.08024577879816629
In [44]:
data.GROUP.value_counts(sort=False)
Out[44]:
0 35 1 157 2 142 3 156 4 147 5 155 6 61 7 88 Name: GROUP, dtype: int64
In [104]:
plt.figure(figsize=(90,65))
sns.lmplot(x='cement',y='strength',data=data,hue='GROUP')
plt.show()
# It can be seen that, Group 4 can predict the strength well (a perfect linear line)
# Group 1, 2, 5, 6, 7 gaussians are highly overlapping with eachother
# group 0 has very high variaance and is scattered.
# Group 0 & group 3 have high strength and high cement content
# Group 3 line is almost horizontal, which means it is a poor predictor of strength
# Group 2 has low cement and low strength content
<Figure size 6480x4680 with 0 Axes>
In [106]:
plt.figure(figsize=(90,65))
sns.lmplot(x='slag',y='strength',data=data,hue='GROUP')
plt.show()
# Except for group 2, 4 and group 7, almost all the lines are "horizontal",
# which means "slag" itself is not much of a good predictor
# Group 2 has very high variance. Group 1 is biased towards '0'
<Figure size 6480x4680 with 0 Axes>
In [105]:
plt.figure(figsize=(90,65))
sns.lmplot(x='ash',y='strength',data=data,hue='GROUP')
plt.show()
# Group 3 has high strength
# Group 3 line is horizontal. Hence it is a bad predictor of strength
# group 1,5,7 have high ash content, however the gaussians over lap eachother. The variance is very high
# Group 4, 6 have high bias towards '0'
# This all the clusters in general have high variance
<Figure size 6480x4680 with 0 Axes>
In [103]:
plt.figure(figsize=(90,65))
sns.lmplot(x='water',y='strength',data=data,hue='GROUP')
plt.show()
# clusters with high water content have low compressive strength.
# Group 5 seems to a better predictor.
# Group 1, 2, 4, 6 are overlapping clusters. They belong to the "high water" content zone
# Group 0, 3 have high strength and low water content. Howevwer,0&3 overlap eachother
# Group 3 line is almost horizontal, which means it is a bad predictor of strength
# Whereas group 0 & 7 seem to be a good predictor
<Figure size 6480x4680 with 0 Axes>
In [108]:
plt.figure(figsize=(90,65))
sns.lmplot(x='superplastic',y='strength',data=data,hue='GROUP')
plt.show()
# Group 0, 3 are horizontal. Which means they are a very bad predictor of strength
# Group 7 seems to be a good predictor of strength
# Group 1, 5, 2 seem to have very high variance and overlap eachother
<Figure size 6480x4680 with 0 Axes>
In [109]:
plt.figure(figsize=(90,65))
sns.lmplot(x='age',y='strength',data=data,hue='GROUP')
plt.show()
# All the group in the age vs strength predictor have very very high variance, which may result in poor prediction
# But it can bee seen that, higher the age, high the average compressive strength
<Figure size 6480x4680 with 0 Axes>
In [111]:
plt.figure(figsize=(90,65))
sns.lmplot(x='coarseagg_perkg_of_fineagg',y='strength',data=data,hue='GROUP')
plt.show()
# Group 3, 7, 1, 5 all have almost horizontal lines. Hence they are poor predictors of strength
# Group 6, 0 seems to be a good predictor of strength
# Group 2 and 4 have very high variance and the overlap eachother
# Groups with high strength have high coarse_agg /- kg of fine_agg ratio
# Groups with low coarse_agg/fine_agg ratio have low strength
<Figure size 6480x4680 with 0 Axes>
In [45]:
data.head(10)
Out[45]:
| cement | slag | ash | water | superplastic | age | coarseagg_perkg_of_fineagg | strength | GROUP | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 0.0 | 28 | 1.298330 | 29.89 | 2 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 10.8 | 14 | 1.357448 | 23.51 | 5 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 5.5 | 28 | 1.111124 | 29.22 | 1 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 0.0 | 28 | 1.391045 | 45.85 | 2 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 9.1 | 28 | 1.503373 | 18.29 | 2 |
| 5 | 255.0 | 0.0 | 0.0 | 192.0 | 0.0 | 90 | 0.941587 | 21.86 | 6 |
| 6 | 166.8 | 250.2 | 0.0 | 203.5 | 0.0 | 7 | 1.408605 | 15.75 | 2 |
| 7 | 251.4 | 0.0 | 118.3 | 188.5 | 6.4 | 56 | 1.357265 | 36.64 | 1 |
| 8 | 296.0 | 0.0 | 0.0 | 192.0 | 0.0 | 28 | 1.418301 | 21.65 | 4 |
| 9 | 155.0 | 184.0 | 143.0 | 194.0 | 9.0 | 28 | 1.258941 | 28.99 | 1 |
In [46]:
X = data.iloc[:,0:-2].values
Y = data.iloc[:,-2].values
In [47]:
X_train,X_test,y_train,y_test = train_test_split(X,Y,random_state=seed,test_size=0.3)
ss = StandardScaler()
X_train_scaled = ss.fit_transform(X_train)
LINEAR REGRESSION¶
In [48]:
lr = LinearRegression()
lr.fit(X_train_scaled,y_train)
X_test_scaled = ss.transform(X_test)
lr.score(X_test_scaled,y_test)
Out[48]:
0.7698899896131519
In [51]:
lr.score(X_train_scaled,y_train)
Out[51]:
0.76668312368894
In [49]:
for i in range(0,len(list(data.columns)[0:-2])):
print("The coefficient of {} is {:.2f}".format(list(data.columns)[0:-2][i],list(lr.coef_)[i]))
print("\nThe intercept is {0:.2f}".format(lr.intercept_))
# The model doesn't seem to be over fit. Hence A simple linear model is ideal for performing prediction.
# The feature importance obtained accoring to Linear Regresion, cement, slag and age have high importance,
# however, superplastic and coarseagge_perkg_of_fineagg have least importance
The coefficient of cement is 11.90 The coefficient of slag is 7.72 The coefficient of ash is 4.59 The coefficient of water is -3.50 The coefficient of superplastic is 1.07 The coefficient of age is 8.95 The coefficient of coarseagg_perkg_of_fineagg is -0.30 The intercept is 35.22
In [126]:
y_pred = lr.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
The RMSE score is 8.156183934604678 The R-squared value is 0.722086962642168
RIDGE¶
In [127]:
Ridge = Ridge(alpha=20)
Ridge.fit(X=X_train_scaled,y= y_train)
Ridge.score(X_test_scaled,y_test)
Out[127]:
0.7757692628347718
In [136]:
for i in range(0,len(list(data.columns)[0:-2])):
print("The coefficient of {} is {:.2f}".format(list(data.columns)[0:-2][i],list(Ridge.coef_)[i]))
# The coef_ seems to be "suppressed" when comapred with lineara regression
# Like linear regression, Ridge coeeficients also say that, coarseagg_perkg and superplastic have the least importance
# cement, slag, ash, age, water have high importance
The coefficient of cement is 10.86 The coefficient of slag is 6.77 The coefficient of ash is 3.54 The coefficient of water is -3.29 The coefficient of superplastic is 1.76 The coefficient of age is 8.63 The coefficient of coarseagg_perkg_of_fineagg is -0.07
In [130]:
y_pred = Ridge.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# R-squared value is less when compared with simple lineaar regression model
The RMSE score is 8.051315171099834 The R-squared value is 0.7052588413769745
LASSO¶
In [131]:
lasso = Lasso(alpha=0.5)
lasso.fit(X_train_scaled,y_train)
lasso.score(X_test_scaled,y_test)
Out[131]:
0.7741677860373652
In [135]:
for i in range(0,len(list(data.columns)[0:-2])):
print("The coefficient of {} is {:.2f}".format(list(data.columns)[0:-2][i],list(lasso.coef_)[i]))
The coefficient of cement is 9.98 The coefficient of slag is 5.75 The coefficient of ash is 2.40 The coefficient of water is -2.95 The coefficient of superplastic is 2.14 The coefficient of age is 8.33 The coefficient of coarseagg_perkg_of_fineagg is 0.00
In [137]:
y_pred = lasso.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
The RMSE score is 8.080015638127835 The R-squared value is 0.6713076782176639
In [138]:
# Let us try predicting the score after removing the least important columns (coarse_agg/fine_agg & superplastic)
In [143]:
data_rem = data.copy()
data_rem.drop({'superplastic','coarseagg_perkg_of_fineagg','GROUP'},axis=1,inplace=True)
In [144]:
data_rem
Out[144]:
| cement | slag | ash | water | age | strength | |
|---|---|---|---|---|---|---|
| 0 | 141.3 | 212.0 | 0.0 | 203.5 | 28 | 29.89 |
| 1 | 168.9 | 42.2 | 124.3 | 158.3 | 14 | 23.51 |
| 2 | 250.0 | 0.0 | 95.7 | 187.4 | 28 | 29.22 |
| 3 | 266.0 | 114.0 | 0.0 | 228.0 | 28 | 45.85 |
| 4 | 154.8 | 183.4 | 0.0 | 193.3 | 28 | 18.29 |
| ... | ... | ... | ... | ... | ... | ... |
| 936 | 141.3 | 212.0 | 0.0 | 203.5 | 7 | 10.39 |
| 937 | 297.2 | 0.0 | 117.5 | 174.8 | 3 | 21.91 |
| 938 | 135.0 | 0.0 | 166.0 | 180.0 | 28 | 13.29 |
| 939 | 276.4 | 116.0 | 90.3 | 179.6 | 28 | 44.28 |
| 940 | 540.0 | 0.0 | 0.0 | 173.0 | 7 | 52.61 |
941 rows × 6 columns
In [165]:
X_rem = data_rem.iloc[:,0:-1]
Y_rem = data_rem.iloc[:,-1]
In [166]:
X_train_rem,X_test_rem,y_train_rem,y_test_rem = train_test_split(X_rem,Y_rem,random_state=seed,test_size=0.3)
ss = StandardScaler()
X_train_scaled = ss.fit_transform(X_train_rem)
In [168]:
lr = LinearRegression()
lr.fit(X_train_scaled,y_train_rem)
X_test_scaled = ss.transform(X_test_rem)
print("The linear regression score is: ",lr.score(X_test_scaled,y_test_rem))
The linear regression score is: 0.7661598201751117
In [152]:
y_pred = lr.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test_rem)))
print("The R-squared value is ",r2_score(y_pred,y_test_rem))
The RMSE score is 8.22202557578397 The R-squared value is 0.7137860326505019
In [153]:
# It is clear that, even after removing 2 columns, there is not much difference in the r2_Score or the RMSE value
In [156]:
Ridge.fit(X=X_train_scaled,y= y_train_rem)
print("The Ridge regression score is: ",Ridge.score(X_test_scaled,y_test_rem))
y_pred = Ridge.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test_rem)))
print("The R-squared value is ",r2_score(y_pred,y_test_rem))
The Ridge regression score is: 0.7709752691414978 The RMSE score is 8.13692749047857 The R-squared value is 0.6920758980156998
In [159]:
lasso.fit(X_train_scaled,y_train_rem)
print("The Lasso regression score is: ",lasso.score(X_test_scaled,y_test_rem))
y_pred = lasso.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test_rem)))
print("The R-squared value is ",r2_score(y_pred,y_test_rem))
The Lasso regression score is: 0.7688630619554074 The RMSE score is 8.174363254179184 The R-squared value is 0.656242814100501
In [160]:
# Let us find the feature importance via decision tree also
DECISION TREE¶
In [183]:
dtree = DecisionTreeRegressor(max_depth=6,random_state=seed)
dtree.fit(X_train_scaled,y_train)
dtree.score(X_test_scaled,y_test)
Out[183]:
0.8275972034590776
In [184]:
y_pred = dtree.predict(X_test_scaled)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# Decision tree by far, has the highest R-squared value and score
The RMSE score is 7.059783913503827 The R-squared value is 0.7882355821632734
In [185]:
dtree.feature_importances_
Out[185]:
array([0.39048105, 0.10109264, 0.00481133, 0.11897449, 0.02171958,
0.35284252, 0.0100784 ])
In [195]:
for i in range(0,len(list(data.columns)[0:-2])):
print("The feature importance of {} is {:.4f}".format(list(data.columns)[i],dtree.feature_importances_[i]))
# In addition to coarseagg_perkg_of_fineagg and superplastic, 'ash' also does not have much of an importance
The feature importance of cement is 0.3905 The feature importance of slag is 0.1011 The feature importance of ash is 0.0048 The feature importance of water is 0.1190 The feature importance of superplastic is 0.0217 The feature importance of age is 0.3528 The feature importance of coarseagg_perkg_of_fineagg is 0.0101
In [197]:
data_rem_dtree=data_rem.copy()
data_rem_dtree.drop('ash',axis=1,inplace=True)
In [200]:
X_rem = data_rem_dtree.iloc[:,0:-1]
Y_rem = data_rem_dtree.iloc[:,-1]
X_train_rem,X_test_rem,y_train_rem,y_test_rem = train_test_split(X_rem,Y_rem,random_state=seed,test_size=0.3)
ss = StandardScaler()
X_train_scaled_rem = ss.fit_transform(X_train_rem)
X_test_scaled_rem = ss.transform(X_test_rem)
dtree = DecisionTreeRegressor(max_depth=6,random_state=seed)
dtree.fit(X_train_scaled_rem,y_train_rem)
dtree.score(X_test_scaled_rem,y_test_rem)
Out[200]:
0.8185156774262545
In [201]:
y_pred = dtree.predict(X_test_scaled_rem)
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test_rem)))
print("The R-squared value is ",r2_score(y_pred,y_test_rem))
# There is not a huge difference in score after dropping '3' attributes
The RMSE score is 7.243339020095123 The R-squared value is 0.7711440856159515
In [ ]:
# The target column in this dataset has continious variables. Hence this requires a "regression" model "only"
# The suitable algorithms are:
# Linear Regression
# Ridge
# Lasso
# Decision Tree Regressor
# Support Vector Regressor
# KNN Regressor
# Adaboost regression
# Gradient boosting regressor
# Random Forest regressor
LINEAR REGRESSION¶
In [412]:
X = data.iloc[:,0:-2].values
Y = data.iloc[:,-2].values
X_train,X_test,y_train,y_test = train_test_split(X,Y,random_state=seed,test_size=0.3)
ss = StandardScaler()
X_train_scaled = ss.fit_transform(X_train)
X_test_scaled = ss.transform(X_test)
In [413]:
lr = LinearRegression()
lr.fit(X_train_scaled,y_train)
y_pred = lr.predict(X_test_scaled)
print("The linear regression score is: ",lr.score(X_test_scaled,y_test_rem))
mse = mean_squared_error
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
The linear regression score is: 0.7698899896131519 The RMSE score is 8.156183934604678 The R-squared value is 0.722086962642168
In [414]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
lr = LinearRegression()
lr.fit(X_train_scaled, y_train)
y_pred = lr.predict(X_test_scaled)
scores.append(lr.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [415]:
print("The mean score is: ",np.mean(scores))
print("The standard deviation is: ",np.std(scores))
print("\nThe mean RMSE is: ",np.mean(RMSE))
print("The standard deviation is: ",np.std(RMSE))
print("\nThe mean r2_score is: ",np.mean(r2))
print("The standard deviation is: ",np.std(r2))
The mean score is: 0.7543197584259589 The standard deviation is: 0.052381093843459084 The mean RMSE is: 8.008431840654229 The standard deviation is: 0.7793264656587777 The mean r2_score is: 0.6775137041592925 The standard deviation is: 0.07055370333059073
In [435]:
model= "Linear Regression"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
64.96% to 85.91% 6.45 to 9.57 0.54 to 0.82
In [436]:
a = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'64.96% to 85.91%','RMSE':'6.45 to 9.57','R-squared':'0.54 to 0.82'} ,index=[1])
a
Out[436]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 1 | Linear Regression | 64.96% to 85.91% | 6.45 to 9.57 | 0.54 to 0.82 |
RIDGE¶
In [322]:
param_grid = {
'alpha':[0.1,0.5,1,2,5,10,20,25,40,50,100,200,400,500,1000],
'tol':[0.001],
'solver':['auto', 'svd', 'cholesky', 'lsqr', 'sparse_cg', 'sag', 'saga'],
'random_state':[seed]
}
In [324]:
grid = GridSearchCV(Ridge(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 35 candidates, totalling 175 fits [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001, score=0.751, total= 0.1s [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=auto, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=svd, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.1, random_state=10, solver=cholesky, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001, score=0.751, total= 0.0s
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=lsqr, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.1, random_state=10, solver=sparse_cg, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.1, random_state=10, solver=sag, tol=0.001, score=0.736, total= 0.0s [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.1, random_state=10, solver=saga, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=auto, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=svd, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001 .......... [CV] alpha=0.5, random_state=10, solver=cholesky, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=lsqr, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001 ......... [CV] alpha=0.5, random_state=10, solver=sparse_cg, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001 ............... [CV] alpha=0.5, random_state=10, solver=sag, tol=0.001, score=0.735, total= 0.0s [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001, score=0.751, total= 0.0s [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001, score=0.772, total= 0.0s [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001, score=0.759, total= 0.0s [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001, score=0.813, total= 0.0s [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001 .............. [CV] alpha=0.5, random_state=10, solver=saga, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=auto, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=auto, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=auto, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=auto, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=auto, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=svd, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=svd, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=svd, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=svd, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=svd, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=1, random_state=10, solver=cholesky, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=lsqr, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=1, random_state=10, solver=sparse_cg, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=sag, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=sag, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=sag, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=sag, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=1, random_state=10, solver=sag, tol=0.001, score=0.735, total= 0.0s [CV] alpha=1, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=saga, tol=0.001, score=0.751, total= 0.0s [CV] alpha=1, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=saga, tol=0.001, score=0.772, total= 0.0s [CV] alpha=1, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=saga, tol=0.001, score=0.759, total= 0.0s [CV] alpha=1, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=saga, tol=0.001, score=0.813, total= 0.0s [CV] alpha=1, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=1, random_state=10, solver=saga, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=auto, tol=0.001, score=0.751, total= 0.0s [CV] alpha=2, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=auto, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=auto, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=auto, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=auto, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=svd, tol=0.001, score=0.751, total= 0.0s [CV] alpha=2, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=svd, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=svd, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=svd, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=svd, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001, score=0.751, total= 0.0s [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=2, random_state=10, solver=cholesky, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001, score=0.752, total= 0.0s [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=lsqr, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001, score=0.751, total= 0.0s [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=2, random_state=10, solver=sparse_cg, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=sag, tol=0.001, score=0.752, total= 0.0s [CV] alpha=2, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=sag, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=sag, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=sag, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=2, random_state=10, solver=sag, tol=0.001, score=0.735, total= 0.0s [CV] alpha=2, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=saga, tol=0.001, score=0.752, total= 0.0s [CV] alpha=2, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=saga, tol=0.001, score=0.772, total= 0.0s [CV] alpha=2, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=saga, tol=0.001, score=0.759, total= 0.0s [CV] alpha=2, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=saga, tol=0.001, score=0.813, total= 0.0s [CV] alpha=2, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=2, random_state=10, solver=saga, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=auto, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=auto, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=auto, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=auto, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=auto, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=auto, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=svd, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=svd, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=svd, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=svd, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=svd, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=svd, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001 ............ [CV] alpha=5, random_state=10, solver=cholesky, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=lsqr, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001 ........... [CV] alpha=5, random_state=10, solver=sparse_cg, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=sag, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=sag, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=sag, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=sag, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=sag, tol=0.001 ................. [CV] alpha=5, random_state=10, solver=sag, tol=0.001, score=0.735, total= 0.0s [CV] alpha=5, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=saga, tol=0.001, score=0.752, total= 0.0s [CV] alpha=5, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=saga, tol=0.001, score=0.773, total= 0.0s [CV] alpha=5, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=saga, tol=0.001, score=0.758, total= 0.0s [CV] alpha=5, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=saga, tol=0.001, score=0.812, total= 0.0s [CV] alpha=5, random_state=10, solver=saga, tol=0.001 ................ [CV] alpha=5, random_state=10, solver=saga, tol=0.001, score=0.735, total= 0.0s
[Parallel(n_jobs=1)]: Done 175 out of 175 | elapsed: 1.0s finished
Out[324]:
GridSearchCV(cv=None, error_score=nan,
estimator=Ridge(alpha=1.0, copy_X=True, fit_intercept=True,
max_iter=None, normalize=False, random_state=None,
solver='auto', tol=0.001),
iid='deprecated', n_jobs=None,
param_grid={'alpha': [0.1, 0.5, 1, 2, 5], 'random_state': [10],
'solver': ['auto', 'svd', 'cholesky', 'lsqr',
'sparse_cg', 'sag', 'saga'],
'tol': [0.001]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [332]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'alpha': 2, 'random_state': 10, 'solver': 'sag', 'tol': 0.001}
0.7661163587907367
Ridge(alpha=2, copy_X=True, fit_intercept=True, max_iter=None, normalize=False,
random_state=10, solver='sag', tol=0.001)
In [437]:
ridge = Ridge(alpha=2, copy_X=True, fit_intercept=True, max_iter=None, normalize=False,
random_state=10, solver='sag', tol=0.001)
In [438]:
ridge.fit(X_train_scaled,y_train)
print("The score on train data: ",ridge.score(X_train_scaled,y_train))
print("\nThe score on test data: ",ridge.score(X_test_scaled,y_test))
The score on train data: 0.7735123281956078 The score on test data: 0.7302650463418574
In [439]:
y_pred = ridge.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# The r-squared value is very less. This cannot be a suitable model
The RMSE score is 8.664582057553247 The R-squared value is 0.5639314051774779
In [440]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
ridge = Ridge(alpha=2, copy_X=True, fit_intercept=True, max_iter=None, normalize=False,
random_state=10, solver='sag', tol=0.001)
ridge.fit(X_train_scaled, y_train)
y_pred = ridge.predict(X_test_scaled)
scores.append(ridge.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [441]:
print("The mean score is: ",np.mean(scores))
print("The standard deviation is: ",np.std(scores))
print("\nThe mean RMSE is: ",np.mean(RMSE))
print("The standard deviation is: ",np.std(RMSE))
print("\nThe mean r2_score is: ",np.mean(r2))
print("The standard deviation is: ",np.std(r2))
The mean score is: 0.7543240560864403 The standard deviation is: 0.05223064993283098 The mean RMSE is: 8.008833681547875 The standard deviation is: 0.7798619046440464 The mean r2_score is: 0.6754286058253263 The standard deviation is: 0.07072216178360125
In [442]:
model= "Ridge Regression"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
64.99% to 85.88% 6.45 to 9.57 0.53 to 0.82
In [443]:
b = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'64.99% to 85.88%','RMSE':'6.45 to 9.57','R-squared':'0.53 to 0.82'} ,index=[2])
b
Out[443]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 2 | Ridge Regression | 64.99% to 85.88% | 6.45 to 9.57 | 0.53 to 0.82 |
LASSO¶
In [347]:
param_grid = {
'alpha':[0.1,0.5,1,2,5,10,20,25,50,75,100,150,200,300,400,500,750,1000],
'max_iter':[1000],
'tol':[0.0001,0.001,0.01,0.1,1.0],
'random_state':[seed],
'selection':['cyclic','random']
}
In [348]:
grid = GridSearchCV(Lasso(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 180 candidates, totalling 900 fits [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.773, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.756, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.812, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.773, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.756, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.812, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.774, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.755, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.811, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.774, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.809, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.735, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.752, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.772, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.753, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.803, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.754, total= 0.1s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.773, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.756, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.812, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.773, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.756, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.812, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.754, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.774, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.755, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.811, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.736, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.750, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.775, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.741, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.804, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.728, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.460, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.478, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.483, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.484, total= 0.0s [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.372, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.752, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.738, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.729, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.752, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.738, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.729, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.753, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.739, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.730, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.754, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.741, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.730, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.751, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.767, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.742, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.792, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.733, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.752, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.738, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.729, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.752, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.769, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.738, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.796, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.729, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.750, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.768, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.735, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.794, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.728, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.742, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.766, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.724, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.787, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.720, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.460, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.472, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.468, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.460, total= 0.0s [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=0.5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.371, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.724, total= 0.1s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.744, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.702, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.702, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.724, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.745, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.702, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.702, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.727, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.746, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.703, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.757, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.705, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.737, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.751, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.715, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.766, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.712, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.739, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.752, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.720, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.767, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.718, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.724, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.744, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.701, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.702, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.724, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.744, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.701, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.701, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.722, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.743, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.700, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.701, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.718, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.742, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.696, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.755, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.698, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.451, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.456, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.444, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.433, total= 0.0s [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.364, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.675, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.634, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.655, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.675, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.635, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.655, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.675, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.635, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.655, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.681, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.691, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.641, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.661, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.687, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.691, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.643, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.686, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.667, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.675, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.634, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.655, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.675, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.634, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.654, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.674, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.633, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.688, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.654, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.671, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.690, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.629, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.687, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.650, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.424, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.412, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.378, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.380, total= 0.0s [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=2, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.341, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.390, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.368, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.001, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.313, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.01, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.393, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.392, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.144, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.369, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=0.1, score=0.387, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.223, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.201, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.144, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.170, total= 0.0s [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=5, max_iter=1000, random_state=10, selection=random, tol=1.0, score=0.191, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=10, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=20, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=25, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=50, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=75, 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selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=75, 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tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] 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selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=75, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=100, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=150, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 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random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=200, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 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tol=0.1, score=-0.000, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=300, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] 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random_state=10, selection=cyclic, tol=0.1 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] 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selection=random, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=400, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] 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tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=500, 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tol=1.0, score=-0.012, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=500, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=750, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=cyclic, tol=1.0, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.0001, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.001, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.01, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=0.1, score=-0.000, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.012, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.002, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.041, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.029, total= 0.0s [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0 [CV] alpha=1000, max_iter=1000, random_state=10, selection=random, tol=1.0, score=-0.000, total= 0.0s
[Parallel(n_jobs=1)]: Done 900 out of 900 | elapsed: 6.5s finished
Out[348]:
GridSearchCV(cv=None, error_score=nan,
estimator=Lasso(alpha=1.0, copy_X=True, fit_intercept=True,
max_iter=1000, normalize=False, positive=False,
precompute=False, random_state=None,
selection='cyclic', tol=0.0001, warm_start=False),
iid='deprecated', n_jobs=None,
param_grid={'alpha': [0.1, 0.5, 1, 2, 5, 10, 20, 25, 50, 75, 100,
150, 200, 300, 400, 500, 750, 1000],
'max_iter': [1000], 'random_state': [10],
'selection': ['cyclic', 'random'],
'tol': [0.0001, 0.001, 0.01, 0.1, 1.0]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [349]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'alpha': 0.1, 'max_iter': 1000, 'random_state': 10, 'selection': 'cyclic', 'tol': 0.0001}
0.7660362826393158
Lasso(alpha=0.1, copy_X=True, fit_intercept=True, max_iter=1000,
normalize=False, positive=False, precompute=False, random_state=10,
selection='cyclic', tol=0.0001, warm_start=False)
In [444]:
lasso = Lasso(alpha=0.1, copy_X=True, fit_intercept=True, max_iter=1000,
normalize=False, positive=False, precompute=False, random_state=10,
selection='cyclic', tol=0.0001, warm_start=False)
In [445]:
lasso.fit(X_train_scaled,y_train)
print("The score on train data: ",lasso.score(X_train_scaled,y_train))
print("\nThe score on test data: ",lasso.score(X_test_scaled,y_test))
The score on train data: 0.773015076737731 The score on test data: 0.7324464985069783
In [446]:
y_pred = lasso.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# The R-squared value is very high. Not a good model
The RMSE score is 8.629473996755182 The R-squared value is 0.5544851902565268
In [447]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = Lasso(alpha=0.1, copy_X=True, fit_intercept=True, max_iter=1000,
normalize=False, positive=False, precompute=False, random_state=10,
selection='cyclic', tol=0.0001, warm_start=False)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [448]:
print("The mean score is: ",np.mean(scores))
print("The standard deviation is: ",np.std(scores))
print("\nThe mean RMSE is: ",np.mean(RMSE))
print("The standard deviation is: ",np.std(RMSE))
print("\nThe mean r2_score is: ",np.mean(r2))
print("The standard deviation is: ",np.std(r2))
The mean score is: 0.7545798813384772 The standard deviation is: 0.05120172725903837 The mean RMSE is: 8.008166530394938 The standard deviation is: 0.7856899877070387 The mean r2_score is: 0.6663138695052322 The standard deviation is: 0.07170258820199997
In [449]:
model= "Lasso Regression"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
65.22% to 85.70% 6.44 to 9.58 0.52 to 0.81
In [450]:
c = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'65.22% to 85.70%','RMSE':'6.44 to 9.58','R-squared':'0.52 to 0.81'} ,index=[3])
c
Out[450]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 3 | Lasso Regression | 65.22% to 85.70% | 6.44 to 9.58 | 0.52 to 0.81 |
DECISION TREE REGRESSOR¶
In [387]:
param_grid = {
'criterion':["mse", "friedman_mse", "mae"],
'max_depth':[1,2,3,4,5,6,7,8],
'min_samples_split':[2,3,4,5],
'min_samples_leaf':[1,2,3],
'random_state':[seed]
}
In [388]:
grid = GridSearchCV(DecisionTreeRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 288 candidates, totalling 1440 fits [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.158, total= 0.0s
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.158, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.767, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.822, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.767, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.822, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.767, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.822, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.819, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.782, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.823, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.707, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.782, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.823, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.707, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.782, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.823, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.707, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.740, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.782, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.821, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.707, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.748, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.790, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.821, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.712, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.748, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.790, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.821, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.712, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.748, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.790, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.821, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.712, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.748, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.790, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.821, total= 0.0s [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.712, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.752, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.798, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.848, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.817, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.731, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.752, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.849, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.818, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.731, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.752, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.853, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.818, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.732, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.752, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.787, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.852, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.815, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.725, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.776, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.852, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.817, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.705, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.776, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.852, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.817, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.705, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.776, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.852, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.817, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.705, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.769, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.851, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.815, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.701, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.759, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.836, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.816, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.759, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.836, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.816, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.759, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.836, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.816, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.836, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.816, total= 0.0s [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.708, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.803, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.841, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.843, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.765, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.785, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.826, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.843, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.843, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.766, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.815, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.839, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.764, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.785, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.826, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.843, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.841, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.756, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.792, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.846, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.742, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.792, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.846, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.742, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.794, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.792, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.846, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.742, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.793, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.808, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.842, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.737, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.787, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.847, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.787, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.847, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.787, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.847, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.787, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.847, total= 0.0s [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.749, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.853, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.866, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.795, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.841, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.850, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.862, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.788, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.756, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.840, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.848, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.872, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.791, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.762, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.850, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.848, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.871, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.779, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.765, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.839, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.850, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.874, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.779, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.765, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.839, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.850, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.874, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.779, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.765, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.839, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.850, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.874, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.779, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.763, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.844, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.849, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.871, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.765, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.755, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.863, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.883, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.769, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.755, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.863, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.883, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.769, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.755, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.863, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.883, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.769, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.755, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.863, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.883, total= 0.0s [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.769, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.092, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.227, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.269, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.252, total= 0.0s [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.158, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.334, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.453, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.527, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.497, total= 0.0s [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.325, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.574, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.569, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.647, total= 0.0s [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.501, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.613, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.664, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.666, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.767, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.822, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.767, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.822, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.767, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.822, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.819, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.763, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.782, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.823, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.707, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.763, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.782, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.823, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.707, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.763, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.782, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.823, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.707, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.755, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.782, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.821, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.707, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.748, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.790, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.821, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.712, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.748, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.790, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.821, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.712, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.748, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.790, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.821, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.712, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.674, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.748, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.790, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.821, total= 0.0s [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.712, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.752, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.790, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.817, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.731, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.752, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.818, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.731, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.752, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.794, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.853, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.818, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.732, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.752, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.787, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.815, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.725, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.757, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.776, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.817, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.705, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.776, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.817, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.705, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.757, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.776, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.817, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.705, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.785, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.851, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.815, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.701, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.791, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.836, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.816, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.791, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.836, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.816, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.791, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.836, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.816, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.791, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.836, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.816, total= 0.0s [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.708, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.777, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.827, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.845, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.842, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.766, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.785, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.824, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.843, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.843, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.768, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.815, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.847, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.839, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.765, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.785, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.826, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.843, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.841, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.795, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.844, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.846, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.744, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.795, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.844, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.846, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.744, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.795, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.844, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.846, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.744, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.793, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.817, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.842, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.844, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.738, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.787, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.847, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.749, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.787, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.847, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.749, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.787, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.847, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.749, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.787, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.847, total= 0.0s [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.749, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.759, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.869, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.797, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.761, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.841, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.867, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.789, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.756, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.848, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.872, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.792, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.762, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.850, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.848, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.871, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.781, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.765, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.839, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.850, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.874, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.775, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.765, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.839, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.850, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.874, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.775, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.765, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.839, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.850, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.874, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.775, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.764, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.861, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.849, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.871, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.766, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.755, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.883, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.769, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.755, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.883, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.769, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.755, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.883, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.769, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.755, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.852, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.825, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.883, total= 0.0s [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=friedman_mse, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.769, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.306, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.223, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.224, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.263, total= 0.0s [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=1, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.029, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.443, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.436, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.517, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.502, total= 0.0s [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=2, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.295, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.519, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.533, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.637, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.645, total= 0.0s [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=3, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.450, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.718, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.718, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.718, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.718, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.591, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.640, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.714, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.730, total= 0.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.622, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.694, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.695, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.747, total= 0.1s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.694, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.683, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.739, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.704, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.683, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.739, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.704, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.683, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.739, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.704, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.652, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.683, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.741, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.704, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.598, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.682, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.699, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.598, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.682, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.699, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.598, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.682, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.699, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.598, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.682, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.699, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.706, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.750, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.801, total= 0.1s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.779, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.766, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.707, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.750, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.801, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.779, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.766, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.707, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.773, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.801, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.780, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.766, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.716, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.802, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.780, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.766, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.711, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.738, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.808, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.774, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.768, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.711, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.738, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.808, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.774, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.768, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.711, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.738, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.808, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.774, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.768, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.719, total= 0.1s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.732, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.809, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.779, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.769, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.665, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.759, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.795, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.665, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.759, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.795, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.665, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.759, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.795, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.665, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.795, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.770, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.749, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.785, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.824, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.807, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.781, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.739, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.768, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.826, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.817, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.782, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.747, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.767, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.819, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.797, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.782, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.745, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.775, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.818, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.819, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.781, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.829, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.809, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.787, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.829, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.809, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.787, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.748, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.770, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.829, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.809, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.787, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.759, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.772, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.827, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.813, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.783, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.700, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.817, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.807, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.700, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.817, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.807, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.700, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.776, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.817, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.807, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.700, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.776, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.817, total= 0.1s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.807, total= 0.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.799, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.813, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.803, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.853, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=2, random_state=10, score=0.758, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.802, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.786, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.802, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.841, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, random_state=10, score=0.757, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.790, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.792, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.797, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.834, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=4, random_state=10, score=0.760, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.794, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.797, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.798, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.852, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=5, random_state=10, score=0.758, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.799, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.762, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.797, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.849, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=2, random_state=10, score=0.771, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.799, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.762, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.797, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.849, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=3, random_state=10, score=0.771, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.799, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.762, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.797, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.849, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=4, random_state=10, score=0.771, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.811, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.799, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.796, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.840, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=2, min_samples_split=5, random_state=10, score=0.782, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.740, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.796, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.831, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=2, random_state=10, score=0.772, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.740, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.796, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.784, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.831, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=3, random_state=10, score=0.772, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.740, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.796, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.831, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=4, random_state=10, score=0.772, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.740, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.796, total= 0.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.784, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.831, total= 0.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=3, min_samples_split=5, random_state=10, score=0.772, total= 0.1s
[Parallel(n_jobs=1)]: Done 1440 out of 1440 | elapsed: 25.9s finished
Out[388]:
GridSearchCV(cv=None, error_score=nan,
estimator=DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features=None,
max_leaf_nodes=None,
min_impurity_decrease=0.0,
min_impurity_split=None,
min_samples_leaf=1,
min_samples_split=2,
min_weight_fraction_leaf=0.0,
presort='deprecated',
random_state=None,
splitter='best'),
iid='deprecated', n_jobs=None,
param_grid={'criterion': ['mse', 'friedman_mse', 'mae'],
'max_depth': [1, 2, 3, 4, 5, 6, 7, 8],
'min_samples_leaf': [1, 2, 3],
'min_samples_split': [2, 3, 4, 5],
'random_state': [10]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [389]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'criterion': 'friedman_mse', 'max_depth': 8, 'min_samples_leaf': 1, 'min_samples_split': 2, 'random_state': 10}
0.824444067559725
DecisionTreeRegressor(ccp_alpha=0.0, criterion='friedman_mse', max_depth=8,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, presort='deprecated',
random_state=10, splitter='best')
In [451]:
dtree = DecisionTreeRegressor(ccp_alpha=0.0, criterion='friedman_mse', max_depth=8,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=4,
min_weight_fraction_leaf=0.0, presort='deprecated',
random_state=10, splitter='best')
In [452]:
dtree.fit(X_train_scaled,y_train)
print("The score on train data: ",dtree.score(X_train_scaled,y_train))
print("\nThe score on test data: ",dtree.score(X_test_scaled,y_test))
The score on train data: 0.9431828598345041 The score on test data: 0.867421404786551
In [453]:
y_pred = dtree.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# By far, decision tree has the best R-squared value and the lowest RMSE value
The RMSE score is 6.0745723836372605 The R-squared value is 0.8579713115526507
In [454]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = DecisionTreeRegressor(ccp_alpha=0.0, criterion='friedman_mse', max_depth=8,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=4,
min_weight_fraction_leaf=0.0, presort='deprecated',
random_state=10, splitter='best')
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [455]:
print("The mean score is: ",np.mean(scores))
print("The standard deviation is: ",np.std(scores))
print("\nThe mean RMSE is: ",np.mean(RMSE))
print("The standard deviation is: ",np.std(RMSE))
print("\nThe mean r2_score is: ",np.mean(r2))
print("The standard deviation is: ",np.std(r2))
The mean score is: 0.8500374700779542 The standard deviation is: 0.03693117466628787 The mean RMSE is: 6.2320518155280125 The standard deviation is: 0.5137811447625409 The mean r2_score is: 0.8391561348313834 The standard deviation is: 0.03744945873000117
In [456]:
model= "Decision Tree Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
77.62% to 92.39% 5.20 to 7.26 0.76 to 0.91
In [457]:
d = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'77.62% to 92.39%',
'RMSE':'5.20 to 7.26','R-squared':'0.76 to 0.91'} ,index=[4])
d
Out[457]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 4 | Decision Tree Regressor | 77.62% to 92.39% | 5.20 to 7.26 | 0.76 to 0.91 |
In [469]:
param_grid= {
'kernel':['linear', 'poly', 'rbf', 'sigmoid'],
'degree':[2,3],
'gamma':['scale','auto'],
'coef0':[0.0],
'tol':[0.001,0.01,0.1,0.0001,1],
'C':[0.1,0.5,1,5,10,25,50,75,100,200,350,500,750,800,1000],
'epsilon':[0.1,0.01,0.5,1],
}
In [470]:
grid = GridSearchCV(SVR(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 4800 candidates, totalling 24000 fits [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.719, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.058, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.070, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.027, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.069, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.033, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.077, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.216, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.212, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.242, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.227, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.722, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.719, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.069, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.069, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.069, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.064, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.069, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.060, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.068, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.033, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.065, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.077, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.216, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.212, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.227, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.421, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.464, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.360, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.353, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.761, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.724, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.716, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.062, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.033, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.077, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.211, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.227, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.362, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.761, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.724, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.716, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.028, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.058, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.027, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.078, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.034, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.077, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.237, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.237, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.237, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.237, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.212, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.237, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.227, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.462, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.353, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.743, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.072, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.029, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.072, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.029, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.030, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.072, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.029, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.028, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.065, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.076, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.242, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.214, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.226, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.364, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.459, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.459, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.429, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.456, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.743, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.030, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.030, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.028, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.030, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.079, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.060, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.029, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.076, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.241, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.241, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.226, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.460, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.363, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.460, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.363, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.426, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.424, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.460, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.427, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.363, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.457, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.360, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.424, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.717, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.025, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.025, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.071, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.025, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.059, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.071, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.025, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.060, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.067, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.030, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.063, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.076, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.262, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.245, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.225, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.458, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.458, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.717, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.026, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.065, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.026, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.065, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.026, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.059, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.070, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.026, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.065, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.081, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.060, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.067, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.031, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.064, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.076, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.152, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.152, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.152, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.243, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.228, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.152, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.262, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.225, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.429, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.425, total= 0.0s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.356, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.719, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.222, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.294, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.216, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.212, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.242, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.227, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.719, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.216, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.277, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.216, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.277, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.278, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.296, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.288, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.315, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.216, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.277, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.288, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.206, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.282, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.295, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.216, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.238, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.230, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.212, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.227, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.464, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.353, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.714, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.761, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.724, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.716, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.321, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.270, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.321, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.270, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.270, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.321, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.270, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.320, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.225, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.150, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.211, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.238, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.227, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.423, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.362, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.361, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.461, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.421, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.759, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.721, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.714, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.761, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.724, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.716, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.277, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.315, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.314, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.208, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.283, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.294, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.237, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.237, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.237, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.237, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.260, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.212, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.144, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.237, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.227, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.463, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.463, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.462, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.353, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.743, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.319, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.275, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.319, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.275, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.319, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.223, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.275, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.319, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.275, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.318, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.225, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.242, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.150, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.242, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.261, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.214, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.226, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.429, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.424, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.428, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.456, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.743, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.722, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.776, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.713, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.316, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.220, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.316, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.220, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.316, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.219, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.316, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.220, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.296, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.290, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.313, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.223, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.287, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.297, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.241, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.219, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.230, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.260, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.218, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.241, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.261, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.215, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.226, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.460, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.363, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.460, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.363, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.460, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.363, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.427, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.457, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.360, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.741, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.720, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.775, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.715, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.742, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.742, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.720, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.775, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.715, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.717, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.288, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.317, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.271, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.295, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.317, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.271, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.317, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.317, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.271, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.286, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.308, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.224, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.272, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.221, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.151, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.228, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.228, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.151, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.228, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.262, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.217, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.144, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.245, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.225, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.459, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.431, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.458, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.422, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.431, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.365, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.421, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.458, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.354, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.775, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.775, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.741, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.720, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.775, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.715, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.742, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.717, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.715, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.289, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.314, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.289, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.314, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.289, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.314, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.277, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.289, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.314, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.276, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.288, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.313, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.217, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.281, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.295, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.152, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.263, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.152, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.244, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.152, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.243, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.228, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.263, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.221, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.152, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.229, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.262, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.218, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.145, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.244, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.225, total= 0.0s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.429, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.430, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.364, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.425, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.459, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.424, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.356, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.426, total= 0.1s [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.423, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.803, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.075, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.103, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.070, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.164, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.609, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.609, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.609, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.647, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.609, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.654, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.650, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.712, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.681, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.160, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.160, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.160, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.160, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.102, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.070, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.160, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.653, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.653, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.608, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.650, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.604, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.747, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.802, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.074, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.098, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.195, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.062, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.159, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.655, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.655, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.655, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.655, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.647, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.686, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.747, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.802, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.159, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.207, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.159, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.159, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.159, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.103, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.193, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.066, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.162, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.207, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.611, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.604, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.653, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.611, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.651, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.708, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.689, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.078, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.078, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.078, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.162, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.078, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.099, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.195, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.079, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.169, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.642, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.602, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.676, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.726, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.076, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.100, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.163, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.206, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.192, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.078, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.608, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.544, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.645, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.608, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.544, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.645, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.643, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.544, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.608, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.544, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.645, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.603, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.643, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.603, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.713, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.685, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.751, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.751, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.166, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.166, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.199, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.077, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.166, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.102, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.081, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.171, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.204, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.641, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.639, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.535, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.642, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.598, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.721, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.714, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.751, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.751, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.076, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.076, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.198, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.075, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.197, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.076, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.167, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.101, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.196, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.073, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.172, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.205, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.639, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.534, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.685, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.710, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.0s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.505, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.536, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.505, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.536, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.505, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.505, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.536, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.609, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.654, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.609, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.609, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.654, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.609, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.654, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.650, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.681, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.803, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.502, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.502, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.501, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.502, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.499, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.653, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.605, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.647, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.608, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.650, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.604, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.723, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.719, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.675, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.749, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.747, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.802, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.504, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.504, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.510, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.581, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.503, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.537, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.582, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.504, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.508, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.581, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.496, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.655, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.655, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.655, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.610, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.655, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.647, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.653, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.605, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.712, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.686, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.747, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.802, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.544, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.611, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.604, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.654, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.610, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.653, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.611, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.654, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.604, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.651, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.604, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.711, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.708, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.689, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.581, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.534, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.581, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.534, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.581, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.535, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.581, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.534, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.509, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.500, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.536, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.644, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.646, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.606, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.607, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.543, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.543, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.642, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.602, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.539, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.646, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.710, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.719, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.726, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.805, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.805, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.749, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.579, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.538, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.509, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.578, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.494, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.608, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.544, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.645, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.608, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.544, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.645, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.643, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.607, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.544, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.644, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.608, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.544, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.645, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.606, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.603, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.643, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.603, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.676, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.711, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.683, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.713, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.676, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.750, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.731, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.510, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.580, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.498, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.533, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.540, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.498, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.533, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.498, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.533, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.510, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.580, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.498, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.533, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.540, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.509, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.576, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.492, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.536, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.641, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.541, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.600, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.541, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.641, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.639, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.535, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.642, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.598, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.723, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.709, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.677, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.721, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.714, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.680, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.750, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.751, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.751, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.804, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.804, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.731, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.577, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.577, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.539, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.510, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.577, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.496, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.538, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.511, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.577, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.497, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.537, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.539, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.508, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.575, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.496, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.539, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.537, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.542, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.640, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.601, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.542, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.640, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.601, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.639, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.534, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.641, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.597, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.723, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.723, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.723, total= 0.0s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.710, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.720, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.711, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.684, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.725, total= 0.1s [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=0.5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.752, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.129, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.129, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.129, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.189, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.129, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.133, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.235, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.765, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.675, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.769, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.713, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.753, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.752, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.806, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.101, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.267, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.129, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.190, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.129, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.267, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.128, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.129, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.237, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.100, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.128, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.731, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.677, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.765, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.686, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.654, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.686, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.698, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.689, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.751, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.131, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.187, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.131, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.187, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.101, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.131, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.131, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.187, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.100, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.271, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.189, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.678, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.765, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.737, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.765, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.727, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.766, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.697, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.656, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.751, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.130, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.130, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.130, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.130, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.188, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.099, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.271, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.126, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.193, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.767, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.691, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.682, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.721, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.752, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.127, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.268, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.190, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.102, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.269, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.122, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.732, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.193, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.128, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.193, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.266, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.127, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.193, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.236, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.101, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.266, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.128, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.193, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.237, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.102, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.130, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.189, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.235, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.732, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.763, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.696, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.677, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.699, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.674, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.718, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.655, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.103, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.269, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.120, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.103, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.269, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.120, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.104, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.269, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.120, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.193, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.237, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.103, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.269, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.120, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.192, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.237, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.105, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.270, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.118, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.198, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.234, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.729, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.678, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.713, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.691, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.675, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.698, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.689, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.104, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.120, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.104, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.120, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.192, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.104, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.267, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.120, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.193, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.237, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.104, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.267, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.120, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.192, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.237, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.106, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.266, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.118, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.199, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.235, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.713, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.681, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.713, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.692, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.697, total= 0.0s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.658, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.752, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.659, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.598, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.659, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.597, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.616, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.659, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.597, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.659, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.598, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.656, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.593, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.617, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.574, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.675, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.769, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.713, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.685, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.654, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.752, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.657, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.596, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.596, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.596, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.596, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.573, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.656, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.592, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.573, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.731, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.731, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.731, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.731, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.677, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.765, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.686, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.684, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.654, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.686, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.698, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.689, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.751, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.616, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.616, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.616, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.657, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.616, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.574, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.592, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.617, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.574, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.737, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.765, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.727, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.766, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.693, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.727, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=0.656, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.808, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.751, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.806, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.656, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.656, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.656, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.656, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.595, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.621, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.578, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.573, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.655, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.593, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.622, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.736, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.736, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.737, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.676, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.767, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.710, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.731, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.691, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.682, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.721, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.660, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.614, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.660, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.614, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.660, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.597, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.614, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.577, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.660, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.597, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.614, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.574, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.658, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.592, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.732, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.735, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.732, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.711, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.694, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.697, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.685, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.752, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.730, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.658, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.618, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.578, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.658, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.618, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.658, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.618, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.578, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.658, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.595, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.618, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.577, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.657, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.594, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.620, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.575, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.763, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.763, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.732, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.763, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.735, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.732, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.679, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.763, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.711, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.710, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.695, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.677, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.653, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.699, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.693, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.729, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.754, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.807, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.580, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.664, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.592, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.615, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.580, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.664, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.591, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.580, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.663, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.591, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.616, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.580, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.664, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.592, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.615, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.580, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.661, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.587, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.617, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.680, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.729, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.764, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.713, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.691, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.675, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.690, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.676, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.698, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.689, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.674, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.724, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.754, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.753, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.807, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.729, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.581, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.661, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.589, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.620, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.581, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.661, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.589, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.620, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.576, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.581, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.661, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.589, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.620, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.581, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.661, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.589, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.620, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.576, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.581, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.660, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.585, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.620, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.575, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.713, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.733, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.734, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.681, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.762, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.712, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.733, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.762, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.712, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.734, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.730, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.680, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.764, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.713, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.678, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.718, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=0.654, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.696, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.692, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.679, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.720, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=0.655, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.696, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.692, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.678, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.718, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=0.654, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.697, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.697, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.678, total= 0.0s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.722, total= 0.1s [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=0.658, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.040, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.226, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.040, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.226, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.039, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.162, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.202, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.040, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.163, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.035, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.317, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.159, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.191, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.836, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.565, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.862, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.561, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.502, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.159, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.568, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-2.556, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.853, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.962, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.502, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-2.155, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.040, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.162, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.226, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.040, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.162, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.040, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.321, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.162, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.202, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.040, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.320, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.162, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.226, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.202, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.043, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.317, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.164, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.224, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.196, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.808, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.621, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.496, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.781, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.910, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.628, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.379, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-2.460, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.781, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.613, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-2.193, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.037, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.321, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.205, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.037, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.321, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.204, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.037, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.320, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.162, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.202, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.037, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.321, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.205, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.038, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.313, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.166, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.224, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.201, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.833, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.557, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.555, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.250, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.938, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.314, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-2.550, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.263, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.944, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.633, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-2.290, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.037, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.321, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.205, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.037, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.321, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.204, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.037, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.320, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.162, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.203, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.037, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.321, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.163, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.205, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.041, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.318, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.160, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.200, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.808, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.857, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.558, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.557, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.777, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.898, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.551, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.293, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.558, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-2.416, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.796, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.851, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.587, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-2.282, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.039, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.314, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.159, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.228, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.206, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.039, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.314, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.159, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.228, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.206, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.039, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.313, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.160, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.230, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.205, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.039, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.314, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.159, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.206, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.038, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.310, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.162, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.230, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.204, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.831, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.958, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.296, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.959, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.297, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.245, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.840, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.957, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.505, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.298, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.958, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.296, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-2.254, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.842, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.947, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.512, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-2.284, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.039, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.314, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.160, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.206, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.039, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.314, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.160, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.206, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.040, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.160, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.228, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.206, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.039, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.314, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.160, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.227, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.206, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.041, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.310, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.163, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.235, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.201, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.854, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.831, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.266, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.267, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.269, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.199, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.895, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.621, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.266, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-2.294, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.224, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.899, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.652, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-2.146, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.046, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.312, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.169, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.224, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.203, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.046, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.312, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.169, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.224, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.203, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.047, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.169, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.224, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.202, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.046, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.312, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.169, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.224, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.203, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.049, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.309, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.166, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.222, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.197, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.853, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.830, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.830, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.851, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.831, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.829, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.483, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.888, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.485, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.292, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.483, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.887, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.484, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.292, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.476, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.886, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.954, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.483, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.294, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.483, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.888, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.485, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.292, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-2.470, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.850, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.475, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-2.280, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.046, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.168, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.225, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.203, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.046, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.168, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.225, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.203, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.047, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.169, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.226, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.203, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.046, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.312, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.168, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.225, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.203, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.054, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.313, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.164, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.234, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.199, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.853, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.830, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.829, total= 0.0s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.335, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.816, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.832, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.573, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.420, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-2.354, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.747, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.677, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-2.340, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.669, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.731, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.624, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.836, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.565, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.862, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.561, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.502, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.159, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.568, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.861, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.963, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.504, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.161, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-2.556, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.962, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1.502, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-2.155, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.680, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.680, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.708, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.673, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.632, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.621, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.496, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.781, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.910, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.628, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.379, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.494, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.779, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.908, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.306, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-2.460, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.781, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1.613, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-2.193, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.626, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.681, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.625, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.678, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.732, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.624, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.834, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.557, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.555, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.250, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.938, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.314, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.567, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.253, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.319, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-2.550, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.263, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.944, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1.633, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-2.290, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.711, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.677, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.711, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.681, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.711, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.677, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.711, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.626, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.676, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.706, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.624, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.808, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.857, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.558, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.557, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.777, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.898, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.551, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.293, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.368, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.776, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.558, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.291, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-2.416, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.796, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.851, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1.587, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-2.282, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.716, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.635, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.635, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.635, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.716, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.731, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.635, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.673, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.633, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.834, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.831, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.958, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.296, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.959, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.297, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.245, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.840, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.957, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.505, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.298, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.242, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.838, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.958, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.511, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.296, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-2.254, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.842, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.947, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1.512, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-2.284, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.728, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.635, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.674, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.715, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.636, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.634, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.671, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.711, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.671, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.733, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.636, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.810, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.835, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.834, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.873, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.831, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.266, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.267, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.269, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.199, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.895, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.621, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.266, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.195, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.897, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.605, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.129, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-2.294, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.224, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.899, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1.652, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-2.146, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.685, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.643, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.685, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.643, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.674, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.685, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.643, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.685, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.643, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.682, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.732, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.638, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.810, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.851, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.831, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.829, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.483, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.888, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1.485, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-2.292, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.483, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.887, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1.484, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-2.292, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.476, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.886, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.954, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1.483, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-2.294, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.483, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.888, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.952, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1.485, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-2.292, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-2.470, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.850, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.937, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1.475, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-2.280, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.730, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.730, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.684, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.642, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.684, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.642, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.684, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.735, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.642, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.675, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.717, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.684, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.734, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.642, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.671, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.713, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.682, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.735, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.639, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.809, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.830, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.830, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.830, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.809, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.829, total= 0.0s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.335, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.816, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.832, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1.573, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-2.420, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.336, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.820, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.828, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1.572, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-2.421, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-2.354, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.747, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.677, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1.622, total= 0.1s [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=5, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-2.340, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.726, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.227, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.228, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.160, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.227, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.227, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.033, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.314, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.158, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.237, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.178, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.946, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.678, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.947, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.643, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.788, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.960, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.946, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-12.591, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-10.787, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11.568, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-9.872, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11.097, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.726, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.313, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.228, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.228, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.161, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.228, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.180, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.031, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.313, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.161, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.228, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.026, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.312, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.156, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.233, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.175, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14.357, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.952, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14.358, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14.358, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.321, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.262, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.918, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.932, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14.357, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.952, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-13.980, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-10.298, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11.251, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-9.931, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11.004, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.315, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.229, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.178, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.315, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.229, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.178, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.033, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.315, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.165, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.229, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.315, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.229, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.178, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.028, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.310, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.159, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.228, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.183, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.216, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.216, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.218, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.670, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.178, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.808, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.217, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-12.224, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10.636, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-9.129, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10.766, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-13.115, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.227, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.227, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.033, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.315, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.164, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.228, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.034, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.314, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.165, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.227, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.179, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.027, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.308, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.157, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.228, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.181, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-12.288, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.959, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-12.287, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.293, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.956, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-12.284, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.335, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12.288, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.959, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-12.265, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.330, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-11.368, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.347, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.2s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.309, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.309, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.022, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.308, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.158, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.233, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.309, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.018, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.317, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.162, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.232, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.174, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.822, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.847, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.656, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.385, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.657, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.386, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.339, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.656, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.560, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.660, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.390, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.656, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.385, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-12.260, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-10.682, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11.538, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-12.120, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-9.721, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.308, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.157, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.309, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.157, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.021, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.310, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.157, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.235, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.021, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.308, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.157, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.234, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.175, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.019, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.312, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.164, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.235, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.172, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.822, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.551, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.552, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-12.438, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.799, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.712, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.556, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.551, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-12.476, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-8.675, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-9.922, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-10.231, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-9.743, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.736, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.018, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.181, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.018, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.181, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.019, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.321, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.155, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.236, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.181, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.018, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.181, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.019, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.321, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.155, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.239, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.176, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.826, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.826, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.827, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.846, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.686, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.647, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.689, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.649, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-14.655, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.688, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.667, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.472, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.463, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.686, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.647, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-14.621, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-10.719, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11.574, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-9.477, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11.453, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.736, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.018, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.181, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.018, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.181, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.017, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.321, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.181, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.018, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.323, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.155, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.236, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.181, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.020, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.310, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.157, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.243, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.178, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.826, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.826, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.887, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.846, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.887, total= 0.0s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.411, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14.827, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.409, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.913, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.886, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.887, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-14.801, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-8.271, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-8.814, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-9.847, total= 0.1s [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-11.428, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.726, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.659, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.687, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.722, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.655, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.946, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.678, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.947, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.643, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.788, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.960, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.646, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.677, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.526, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.791, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.946, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-12.591, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-10.787, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11.568, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-9.872, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11.097, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.726, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.689, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.659, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.688, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.722, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.653, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14.357, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.952, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14.358, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14.358, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.321, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.262, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.918, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.932, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14.357, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.327, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.264, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.884, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.952, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-13.980, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-10.298, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11.251, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-9.931, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11.004, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.699, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.699, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.728, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.699, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.721, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.653, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.820, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.216, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.216, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.218, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.670, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.178, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.808, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.217, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.673, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.180, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.804, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-13.130, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-12.224, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10.636, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-9.129, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10.766, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-13.115, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.698, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.661, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.720, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.693, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.760, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.656, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.819, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-12.288, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.959, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-12.287, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.293, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.956, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-12.284, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.335, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12.288, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.332, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.375, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.292, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.959, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-12.265, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.330, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-11.368, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.347, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-10.953, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.663, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.755, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.722, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.694, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.823, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.847, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-12.656, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.385, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-12.657, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.386, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.339, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.656, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.560, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-12.660, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.390, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.336, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.653, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.629, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-12.656, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.385, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-12.260, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-10.682, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11.538, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-12.120, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-9.721, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.772, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.663, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.727, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.695, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.662, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.690, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.722, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.693, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.665, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.823, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.822, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.845, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.551, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.552, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-12.438, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.799, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.712, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.556, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12.439, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.794, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.713, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10.135, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.551, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-12.476, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-8.675, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-9.922, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-10.231, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-9.743, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.2s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.736, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.761, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.761, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.728, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.761, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.761, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.725, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.694, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.673, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.827, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.846, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.647, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10.689, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.649, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-14.655, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10.688, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.667, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-9.472, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11.463, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-14.654, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10.686, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.647, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-9.435, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11.462, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-14.621, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-10.719, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11.574, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-9.477, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11.453, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.736, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.692, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.690, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.726, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.697, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.762, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.674, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.826, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.846, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.826, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.887, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.846, total= 0.0s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11.411, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14.827, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.409, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-8.913, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9.886, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14.828, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.401, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-8.911, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9.887, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11.412, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-14.801, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-8.271, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-8.814, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-9.847, total= 0.1s [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=10, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-11.428, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.247, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.296, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.148, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.247, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.029, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.293, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.150, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.247, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.836, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-95.699, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.594, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.937, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-95.698, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.593, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.938, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-95.696, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.604, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.939, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-86.309, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-95.699, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.594, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.937, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-95.673, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-56.389, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-73.573, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-60.685, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-86.299, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.726, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.298, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.023, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.295, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.025, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.245, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.160, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-93.866, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-65.359, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.121, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-65.358, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.117, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-58.000, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.872, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-65.354, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.737, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-93.866, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-65.359, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-94.163, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-58.017, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-71.871, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-65.347, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-87.652, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.298, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.249, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.166, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.027, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.293, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.151, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.170, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.832, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-96.913, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.643, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-88.068, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-96.913, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.641, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-88.069, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-96.932, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-59.519, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.632, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.941, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-88.060, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-96.912, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.643, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88.068, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-96.949, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-59.511, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-73.597, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-60.951, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-88.110, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.148, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.251, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.148, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.251, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.251, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.148, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.251, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.034, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.288, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.246, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.875, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.156, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.876, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-55.642, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.910, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-63.585, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.704, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.877, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-94.438, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-55.654, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-71.895, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-63.726, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-87.731, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.031, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.160, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.250, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.027, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.291, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.140, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.247, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.155, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.879, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.878, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.860, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-94.216, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.506, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.967, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-87.794, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-94.218, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.507, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.968, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-87.796, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-94.225, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-59.535, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.517, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.980, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-87.592, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-94.216, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.506, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.967, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-87.794, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-94.244, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-59.531, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-73.102, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-60.905, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-87.481, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.291, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.252, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.292, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.293, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.252, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.159, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.291, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.252, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.024, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.289, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.139, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.248, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.861, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.443, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.444, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-96.065, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-57.822, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.758, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-63.746, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.447, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.443, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-95.980, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-58.111, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-71.930, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-65.795, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-87.494, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.735, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.140, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.140, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.028, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.142, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.241, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.156, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.140, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.032, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.300, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.139, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.246, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.167, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.879, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85.191, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-68.544, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-95.194, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85.192, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-68.543, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-66.257, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.465, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85.185, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-68.468, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85.191, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-68.544, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-95.127, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-66.107, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-73.524, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-85.103, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-68.153, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.2s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.735, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.141, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.141, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.028, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.156, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.030, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.141, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.242, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.154, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.031, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.301, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.245, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.165, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.880, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.901, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-94.639, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.584, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-64.898, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.638, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-64.653, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.585, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-64.897, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.643, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.797, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.575, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-64.883, total= 0.0s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-94.639, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.584, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-64.898, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-94.582, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-64.420, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71.800, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71.542, total= 0.1s [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-64.853, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.693, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.729, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.778, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.778, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.693, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.729, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.778, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.687, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.836, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-95.699, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.594, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.937, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-95.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.593, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.938, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-95.696, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.604, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.939, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-86.309, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-95.699, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-56.391, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.594, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.937, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-86.302, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-95.673, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-56.389, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-73.573, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-60.685, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-86.299, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.729, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.707, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.779, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.670, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.729, total= 0.4s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.707, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.779, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.709, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.667, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.833, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.835, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-93.866, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-65.359, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.121, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-65.358, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.117, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-58.000, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.872, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-65.354, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.737, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-93.866, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-57.996, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.883, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-65.359, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-94.163, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-58.017, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-71.871, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-65.347, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-87.652, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.692, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.779, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.709, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.672, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.692, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.779, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.688, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.704, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.670, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-96.913, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.643, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-88.068, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-96.913, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.641, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-88.069, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-96.932, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-59.519, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.632, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.941, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-88.060, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-96.912, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59.520, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.643, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.931, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88.068, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-96.949, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-59.511, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-73.597, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-60.951, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-88.110, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.692, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.778, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.778, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.728, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.779, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.692, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.728, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.708, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.778, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.687, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.706, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.780, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.669, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.857, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.832, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.875, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.156, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.876, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-55.642, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.910, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-63.585, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.704, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-94.157, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-55.641, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.877, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63.581, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.710, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-94.438, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-55.654, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-71.895, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-63.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-87.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.696, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.729, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.710, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.780, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.696, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.710, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.780, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.695, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.730, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.709, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.780, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.673, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.696, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.710, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.780, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.674, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.692, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.783, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.669, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.879, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.860, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-94.216, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.506, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-60.967, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-87.794, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-94.218, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.507, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-60.968, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-87.796, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-94.225, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-59.535, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.517, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-60.980, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-87.592, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-94.216, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59.534, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.506, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60.967, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-87.794, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-94.244, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-59.531, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-73.102, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-60.905, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-87.481, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.696, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.709, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.674, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.696, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.709, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.674, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.695, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.709, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.781, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.673, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.696, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.729, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.709, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.781, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.674, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.693, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.706, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.783, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.837, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.861, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-87.443, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-87.444, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-96.065, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-57.822, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.758, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-63.746, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-87.447, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-96.069, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-57.819, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.760, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63.749, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-87.443, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-95.980, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-58.111, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-71.930, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-65.795, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-87.494, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.735, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.707, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.672, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.707, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.781, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.697, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.725, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.669, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.842, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.841, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.879, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85.191, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-68.544, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-95.194, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85.192, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-68.543, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-66.257, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-73.465, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85.185, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-68.468, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-95.195, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-66.270, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73.469, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85.191, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-68.544, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-95.127, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-66.107, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-73.524, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-85.103, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-68.153, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.735, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.697, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.707, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.672, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.698, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.727, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.707, total= 0.3s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.782, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 0.2s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.699, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.726, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.708, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.670, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.841, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.880, total= 0.0s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-94.639, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71.584, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-64.898, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-94.638, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-64.653, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71.585, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-64.897, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-94.643, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.797, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71.575, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-64.883, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-94.639, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-64.652, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.848, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71.584, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-64.898, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-94.582, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-64.420, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71.800, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71.542, total= 0.1s [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=25, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-64.853, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.071, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.293, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.262, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.159, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.077, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.293, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.148, total= 0.0s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.264, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.153, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-317.755, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-279.963, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-258.891, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-293.919, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-297.838, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-317.755, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-279.964, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-258.893, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-293.918, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-297.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-317.765, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-279.980, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-258.915, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-293.909, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-297.863, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-317.755, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-279.963, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-258.891, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-293.919, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-297.838, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-317.772, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-280.032, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-258.374, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-293.924, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-298.136, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.294, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.071, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.293, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.262, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.070, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.067, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.285, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.148, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.265, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.154, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.838, total= 0.0s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.095, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-218.055, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-223.235, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-239.939, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-292.023, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.094, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-218.055, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-223.236, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-239.934, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-292.020, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.092, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-218.069, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-223.247, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-239.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-292.006, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.095, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-218.054, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-223.234, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-239.939, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-292.023, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-355.050, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-218.346, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-223.381, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-239.093, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-291.872, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.812, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.299, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.150, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.298, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.149, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.073, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.297, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.148, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.264, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.299, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.150, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.080, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.156, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-330.394, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-228.738, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-279.252, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-366.519, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-292.970, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-330.389, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-228.739, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-279.251, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-366.512, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-292.974, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-330.336, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-228.796, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-279.245, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-366.484, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-292.997, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-330.394, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-228.738, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-279.252, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-366.519, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-292.970, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-330.364, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-228.792, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-279.676, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-365.910, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-291.783, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.812, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.298, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.150, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.299, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.149, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.298, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.265, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.074, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.298, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.150, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.263, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.158, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.078, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.297, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.143, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.268, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.162, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.840, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.879, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.105, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-240.029, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.104, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-240.023, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.096, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-214.161, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-273.533, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-240.003, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-230.999, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.105, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-240.029, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-355.086, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-214.508, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-268.584, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-239.265, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-229.799, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.256, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.256, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.063, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.256, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.150, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.256, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.066, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.287, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.258, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.842, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-329.957, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-244.262, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-329.958, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-244.261, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-329.939, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-235.722, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-280.194, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-291.192, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-244.255, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-329.957, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-244.262, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-330.013, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-235.725, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-280.210, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-244.168, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.255, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.255, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.064, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.283, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.256, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.150, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.065, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.145, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.255, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.055, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.282, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.142, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.253, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-228.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-279.335, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-307.766, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-223.715, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-228.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-279.333, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-307.767, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-223.723, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.011, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-228.922, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-279.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-307.788, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-223.746, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-228.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-279.335, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-307.766, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-223.714, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-228.881, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-262.643, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-308.273, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-223.787, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.134, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.155, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.156, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.050, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.133, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.249, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.154, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.294, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.134, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.155, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.056, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.288, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.128, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.154, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.850, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-314.742, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-284.147, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-322.186, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-221.042, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-314.743, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-284.147, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-322.186, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-221.046, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-314.747, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-284.154, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-322.170, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-221.086, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-314.742, total= 0.0s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-234.192, total= 0.0s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-284.146, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-322.185, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-221.041, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-314.775, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-234.838, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-283.831, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-322.112, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-221.205, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.2s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.134, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.155, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.156, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.133, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.247, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.153, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.051, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.295, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.134, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.248, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.155, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.057, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.287, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.132, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.152, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.850, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-231.752, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-272.766, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-239.789, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-237.427, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-231.753, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-272.767, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-239.787, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-237.430, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-354.914, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-231.757, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-272.765, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-239.787, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-237.440, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-231.752, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-272.766, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-239.789, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-237.427, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-354.931, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-231.749, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-272.692, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-239.681, total= 0.1s [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-237.552, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.685, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.783, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.667, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.684, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.783, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.667, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.685, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.667, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.685, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.727, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.783, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.667, total= 0.7s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.682, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.723, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.715, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.667, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-317.755, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-279.963, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-258.891, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-293.919, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-297.838, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-317.755, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-279.964, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-258.893, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-293.918, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-297.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-317.765, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-279.980, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-258.915, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-293.909, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-297.863, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-317.755, total= 0.0s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-279.963, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-258.891, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-293.919, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-297.838, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-317.772, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-280.032, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-258.374, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-293.924, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-298.136, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.685, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.783, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.667, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.685, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.713, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.783, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.667, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.685, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.783, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.667, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.685, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.783, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.667, total= 0.7s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.681, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.724, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.784, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.664, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.838, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.095, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-218.055, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-223.235, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-239.939, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-292.023, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.094, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-218.055, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-223.236, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-239.934, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-292.020, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.092, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-218.069, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-223.247, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-239.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-292.006, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.095, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-218.054, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-223.234, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-239.939, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-292.023, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-355.050, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-218.346, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-223.381, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-239.093, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-291.872, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.812, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.683, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.727, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.711, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.782, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.663, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.683, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.711, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.663, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.682, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.712, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.664, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.683, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.727, total= 0.9s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.711, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.782, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.663, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.679, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.725, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.668, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.880, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-330.394, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-228.738, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-279.252, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-366.519, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-292.970, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-330.389, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-228.739, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-279.251, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-366.512, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-292.974, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-330.336, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-228.796, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-279.245, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-366.484, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-292.997, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-330.394, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-228.738, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-279.252, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-366.519, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-292.970, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-330.364, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-228.792, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-279.676, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-365.910, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-291.783, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.812, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.683, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.711, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.782, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.663, total= 0.6s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.683, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.711, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.664, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.682, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.712, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.782, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.664, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.683, total= 0.7s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.727, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.711, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.782, total= 0.6s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.663, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.680, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.725, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.713, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.669, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.840, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.880, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.840, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.879, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.105, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-240.029, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.104, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-240.023, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.096, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-214.161, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-273.533, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-240.003, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-230.999, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.105, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-214.153, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-273.519, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-240.029, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-230.992, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-355.086, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-214.508, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-268.584, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-239.265, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-229.799, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.692, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.726, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.781, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.670, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.726, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.781, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.670, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.726, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.781, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.671, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.692, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.726, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.781, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.670, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.687, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.721, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.783, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.673, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.842, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-329.957, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-244.262, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-329.958, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-244.261, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-329.939, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-235.722, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-280.194, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-291.192, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-244.255, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-329.957, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-235.715, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-280.196, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-244.262, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-330.013, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-235.725, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-280.210, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-291.195, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-244.168, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.726, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.717, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.781, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.670, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.726, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.717, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.781, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.670, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.726, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.781, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.670, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.692, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.726, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.717, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.781, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.670, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.683, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.724, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.715, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.783, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.843, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.844, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-228.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-279.335, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-307.766, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-223.715, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-228.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-279.333, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-307.767, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-223.723, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-355.011, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-228.922, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-279.295, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-307.788, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-223.746, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-228.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-279.335, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-307.766, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-223.714, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-355.014, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-228.881, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-262.643, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-308.273, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-223.787, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.722, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.719, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.781, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.676, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.722, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.781, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.676, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.691, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.722, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.718, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.781, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.677, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.692, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.722, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.719, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.781, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.676, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.687, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.720, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.780, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.678, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.850, total= 0.0s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-314.742, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-284.147, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-322.186, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-221.042, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-314.743, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-284.147, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-322.186, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-221.046, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-314.747, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-284.154, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-322.170, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-221.086, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-314.742, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-234.192, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-284.146, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-322.185, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-221.041, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-314.775, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-234.838, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-283.831, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-322.112, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-221.205, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.692, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.723, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.781, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.676, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.692, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.723, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.718, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.781, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.676, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.692, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.722, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.781, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.677, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.692, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.723, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 0.4s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.781, total= 0.5s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.676, total= 0.3s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.686, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.721, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.782, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.678, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.2s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.850, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.902, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-231.752, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-272.766, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-239.789, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-237.427, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-231.753, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-272.767, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-239.787, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-237.430, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-354.914, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-231.757, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-272.765, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-239.787, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-237.440, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-354.916, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-231.752, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-272.766, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-239.789, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-237.427, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-354.931, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-231.749, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-272.692, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-239.681, total= 0.1s [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=50, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-237.552, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.289, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.145, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.264, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.082, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.079, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.289, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.143, total= 0.0s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.268, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-716.180, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-682.012, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.958, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-576.402, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-716.183, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-682.011, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.959, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-576.397, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-716.229, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-496.859, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-682.011, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.927, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-576.387, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-716.179, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-682.012, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.958, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-576.402, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-716.445, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-496.864, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-682.056, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-669.950, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-575.961, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.291, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.291, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.081, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.291, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.264, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.079, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.266, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.148, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-806.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-488.482, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.832, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-590.727, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-657.450, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-806.074, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-488.478, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.834, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-590.730, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-657.447, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-806.078, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-488.445, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-590.765, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-657.441, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-806.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-488.482, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.832, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-590.727, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-657.451, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-806.708, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-487.517, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-666.842, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-590.709, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-657.514, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.288, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.288, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.081, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.141, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.288, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.149, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.076, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.140, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.145, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-788.424, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-490.087, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-682.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-523.284, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-788.423, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-490.086, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-682.081, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-523.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-788.422, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-490.073, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-682.071, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.933, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-523.307, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-788.424, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-490.087, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-682.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-523.284, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-788.440, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-490.032, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-682.071, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-669.664, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-523.212, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.081, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.141, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.265, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.082, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.264, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.080, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.272, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.148, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-798.583, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-441.300, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.901, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-566.542, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-798.582, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-441.298, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.903, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-566.561, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-798.589, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-441.276, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.909, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-566.727, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-798.582, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-441.300, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.901, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-566.540, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-798.530, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-441.346, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-666.757, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-567.275, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-517.368, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.7s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.7s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.148, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.076, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.281, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.142, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-630.161, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-681.702, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.988, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-560.326, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-630.159, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-681.701, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.987, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-560.327, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-800.972, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-630.154, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-681.691, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.980, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-560.342, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-630.161, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-681.702, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.988, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-560.326, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-801.059, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-630.127, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-681.654, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-670.173, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-557.806, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.073, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.148, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.071, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.072, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.286, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.143, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.254, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.068, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.279, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.144, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.894, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-805.865, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-688.577, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-587.818, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-589.670, total= 0.0s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-806.215, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-688.573, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-653.272, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-587.817, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-589.674, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-806.196, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-688.567, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-587.800, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-589.712, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-805.864, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-688.577, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-587.818, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-589.670, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-805.993, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-688.419, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-653.291, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-587.193, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-589.597, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.289, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.246, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.246, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.289, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.134, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.246, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.153, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.289, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.246, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.063, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.287, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.252, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.154, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-798.478, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-681.322, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-718.822, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-592.241, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-798.479, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-681.323, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-718.823, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-592.244, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-798.494, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-630.113, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-681.329, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-718.827, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-592.247, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-798.478, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-681.322, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-718.821, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-592.242, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-798.600, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-630.103, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-681.229, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-718.736, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-592.299, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.5s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 0.3s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.289, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.247, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.290, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.247, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.058, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.289, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.135, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.247, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.152, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.289, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.247, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.2s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.057, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.291, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.132, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.151, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-793.878, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-711.344, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.146, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-577.089, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-525.282, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-793.875, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-711.348, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.145, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-577.081, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-525.280, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-793.834, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-711.375, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.158, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-576.556, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-525.255, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-793.879, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-711.344, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.146, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-577.090, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-525.283, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-793.709, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-711.499, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-665.985, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-575.691, total= 0.1s [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-520.640, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.681, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.726, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.783, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.667, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.681, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.726, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.783, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.667, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.682, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.726, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.783, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.666, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.681, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.726, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.783, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.667, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.678, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.724, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.783, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.667, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-716.180, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-682.012, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.958, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-576.402, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-716.183, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-682.011, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.959, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-576.397, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-716.229, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-496.859, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-682.011, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.927, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-576.387, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-716.179, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-496.862, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-682.012, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.958, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-576.402, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-716.445, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-496.864, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-682.056, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-669.950, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-575.961, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.681, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.726, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.782, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.667, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.681, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.726, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.782, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.667, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.682, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.726, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.783, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.666, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.681, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.726, total= 1.0s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.782, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.667, total= 0.8s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.679, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.723, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.782, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.666, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-806.072, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-488.482, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.832, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-590.727, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-657.450, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-806.074, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-488.478, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.834, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-590.730, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-657.447, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-806.078, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-488.445, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-590.765, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-657.441, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-806.072, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-488.482, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.832, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-590.727, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-657.451, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-806.708, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-487.517, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-666.842, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-590.709, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-657.514, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.680, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.726, total= 0.8s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.781, total= 0.9s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.663, total= 0.9s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.680, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.726, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.781, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.663, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.681, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.726, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.781, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.663, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.680, total= 0.9s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.726, total= 0.9s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.781, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.663, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.677, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.724, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.663, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-788.424, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-490.087, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-682.082, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-523.284, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-788.423, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-490.086, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-682.081, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-523.286, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-788.422, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-490.073, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-682.071, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.933, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-523.307, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-788.424, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-490.087, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-682.082, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.952, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-523.284, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-788.440, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-490.032, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-682.071, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-669.664, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-523.212, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.680, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.726, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.781, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.663, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.680, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.726, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.781, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.663, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.680, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.726, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.782, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.663, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.680, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.726, total= 1.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.781, total= 0.8s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.663, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.677, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.724, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.784, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.663, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.848, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.848, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-798.583, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-441.300, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.901, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-566.542, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-798.582, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-441.298, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.903, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-566.561, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-798.589, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-441.276, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.909, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-566.727, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-798.582, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-441.300, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.901, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-566.540, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-517.401, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-798.530, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-441.346, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-666.757, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-567.275, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-517.368, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.687, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.722, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.722, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.781, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.677, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.687, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.722, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.722, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.781, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.677, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.687, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.723, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.722, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.782, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.677, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.687, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.722, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.722, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.781, total= 1.0s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.677, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.679, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.721, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.780, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.677, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-630.161, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-681.702, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-669.988, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-560.326, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-630.159, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-681.701, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-669.987, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-560.327, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-800.972, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-630.154, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-681.691, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-669.980, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-560.342, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-800.977, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-630.161, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-681.702, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-669.988, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-560.326, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-801.059, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-630.127, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-681.654, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-670.173, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-557.806, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.687, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.722, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.722, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.781, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.677, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.687, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.722, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.722, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.781, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.677, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.687, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.722, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.721, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.782, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.677, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.687, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.722, total= 0.7s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.722, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.781, total= 1.4s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.677, total= 0.9s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.680, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.721, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.719, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.781, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.894, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.894, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.865, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-805.865, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-688.577, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-587.818, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-589.670, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-806.215, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-688.573, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-653.272, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-587.817, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-589.674, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-806.196, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-688.567, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-587.800, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-589.712, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-805.864, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-688.577, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-653.273, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-587.818, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-589.670, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-805.993, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-688.419, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-653.291, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-587.193, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-589.597, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.759, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.688, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.720, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.719, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.780, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.679, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.688, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.720, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.719, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.780, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.679, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.689, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.720, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.718, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.779, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.678, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.688, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.720, total= 0.8s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.719, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.780, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.679, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.685, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.716, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.777, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.676, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-798.478, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-681.322, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-718.822, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-592.241, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-798.479, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-681.323, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-718.823, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-592.244, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-798.494, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-630.113, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-681.329, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-718.827, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-592.247, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-798.478, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-630.117, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-681.322, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-718.821, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-592.242, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-798.600, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-630.103, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-681.229, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-718.736, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-592.299, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.759, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.688, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.720, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.719, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.779, total= 0.5s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.679, total= 0.6s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.688, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.720, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.719, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.779, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.679, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.688, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.720, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.718, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.779, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.678, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.688, total= 0.4s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.720, total= 1.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.719, total= 0.3s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.779, total= 1.0s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.679, total= 1.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.685, total= 0.2s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.719, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.777, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.892, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.903, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-793.878, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-711.344, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-666.146, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-577.089, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-525.282, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-793.875, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-711.348, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-666.145, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-577.081, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-525.280, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-793.834, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-711.375, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-666.158, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-576.556, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-525.255, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-793.879, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-711.344, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-666.146, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-577.090, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-525.283, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-793.709, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-711.499, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-665.985, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-575.691, total= 0.1s [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=75, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-520.640, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.8s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.150, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.150, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.088, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.142, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.262, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.149, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.150, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.082, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.287, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.263, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1456.700, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1016.448, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1218.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1238.100, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-891.643, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1456.707, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1016.437, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1218.154, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1238.112, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-891.645, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1456.807, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1016.318, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1218.159, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1238.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-891.658, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1456.700, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1016.449, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1218.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1238.100, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-891.643, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1457.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1015.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1218.217, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1236.424, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-891.817, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.151, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.151, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.283, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.260, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.150, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.087, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.143, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.260, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.151, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.077, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.274, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.144, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.262, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1279.821, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1022.010, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1265.972, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-947.408, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-944.668, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1279.821, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1022.011, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1265.977, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-947.409, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-944.658, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1279.858, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1022.012, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1266.022, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-947.405, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-944.570, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1279.821, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1022.010, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1265.971, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-947.408, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-944.669, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1279.912, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1021.935, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1266.401, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-947.047, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-943.912, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.7s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.090, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.258, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.091, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.258, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.148, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.088, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.282, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.142, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.260, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.146, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.090, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.258, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.082, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.285, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.136, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.262, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.151, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.853, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1456.524, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1016.442, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1218.248, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1220.023, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-889.946, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1456.531, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1016.431, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1218.250, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1220.021, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-889.948, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1456.634, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1016.290, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1218.275, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1220.047, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-889.961, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1456.522, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1016.443, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1218.247, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1220.023, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-889.946, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1457.976, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1015.239, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1218.528, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1219.619, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-890.062, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.090, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.258, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.091, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.258, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.090, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.282, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.142, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.259, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.146, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.090, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.283, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.258, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.086, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.284, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.137, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.263, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.150, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1269.406, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1008.238, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1265.963, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-973.068, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-897.970, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1269.405, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1008.234, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1265.972, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-973.075, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-897.969, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1269.403, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1008.172, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1266.013, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-973.144, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-897.973, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1269.406, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1008.238, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1265.963, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-973.067, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-897.970, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1269.775, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1007.675, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1266.515, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-973.204, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-898.107, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.9s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.141, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.074, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.280, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.141, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.254, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.077, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.145, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.140, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.860, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1399.557, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1107.298, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1217.735, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-938.531, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-886.021, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1399.551, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1107.300, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1217.734, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-938.543, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-886.019, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1399.510, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1107.297, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1217.723, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-938.649, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-886.005, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1399.558, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1107.298, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1217.735, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-938.530, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-886.021, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1406.744, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1109.116, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1217.625, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-939.974, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-885.954, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.141, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.278, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.074, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.281, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.142, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.073, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.277, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.141, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.255, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.074, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.283, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.143, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1410.165, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-967.613, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1272.155, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-961.285, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1065.272, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1410.170, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-967.612, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1272.159, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-961.303, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1065.275, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1410.180, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-967.600, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1272.134, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-961.472, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1065.287, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1410.165, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-967.613, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1272.156, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-961.283, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1065.273, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1417.436, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-967.802, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1271.938, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-962.958, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1063.000, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.8s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.7s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.7s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.8s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.6s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.8s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.289, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.134, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.289, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.134, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.066, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.290, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.136, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.251, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.152, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.289, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.134, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.065, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.289, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.133, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.256, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.151, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.905, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1613.585, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1013.712, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1217.214, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1257.777, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1011.130, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1613.584, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1013.711, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1217.213, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1257.778, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1011.113, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1613.634, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1013.707, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1217.200, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1257.752, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1010.963, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1613.586, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1013.712, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1217.214, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1257.776, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1011.131, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1614.317, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1013.567, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1216.974, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1257.315, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1011.489, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.5s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.289, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.134, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.289, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.134, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.066, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.290, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.136, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.152, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.289, total= 0.2s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.134, total= 0.4s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.250, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.153, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.063, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.286, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.129, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.251, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1435.387, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-875.495, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1190.152, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-920.197, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1014.669, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1435.388, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-875.494, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1190.152, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-920.206, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1014.660, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1435.406, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-875.486, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1190.160, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-920.297, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1014.501, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1435.387, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-875.495, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1190.152, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-920.196, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1014.671, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1436.397, total= 0.1s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-875.208, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1190.078, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-920.828, total= 0.0s [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1014.415, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.724, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.717, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.780, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.669, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.724, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.717, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.669, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.724, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.667, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.676, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.724, total= 1.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.717, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.780, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.669, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.675, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.723, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.668, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1456.700, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1016.448, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1218.153, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1238.100, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-891.643, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1456.707, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1016.437, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1218.154, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1238.112, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-891.645, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1456.807, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1016.318, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1218.159, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1238.146, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-891.658, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1456.700, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1016.449, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1218.153, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1238.100, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-891.643, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1457.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1015.277, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1218.217, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-1236.424, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-891.817, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.676, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.724, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.717, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.779, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.669, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.724, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.717, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.779, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.668, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.724, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.716, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.667, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.675, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.724, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.717, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.779, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.669, total= 1.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.673, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.723, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.780, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.666, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1279.821, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1022.010, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1265.972, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-947.408, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-944.668, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1279.821, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1022.011, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1265.977, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-947.409, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-944.658, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1279.858, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1022.012, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1266.022, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-947.405, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-944.570, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1279.821, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1022.010, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1265.971, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-947.408, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-944.669, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1279.912, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1021.935, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-1266.401, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-947.047, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-943.912, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.771, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.674, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.724, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.716, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.780, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.665, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.674, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.724, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.665, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.672, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.724, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.781, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.666, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.674, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.724, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.716, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.780, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.665, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.676, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.726, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.782, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.664, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1456.524, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1016.442, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1218.248, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-1220.023, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-889.946, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1456.531, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1016.431, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1218.250, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-1220.021, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-889.948, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1456.634, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1016.290, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1218.275, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-1220.047, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-889.961, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1456.522, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1016.443, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1218.247, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1220.023, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-889.946, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1457.976, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1015.239, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1218.528, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-1219.619, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-890.062, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.771, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.674, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.724, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.716, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.780, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.665, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.674, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.724, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.716, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.780, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.665, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.672, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.723, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.716, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.780, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.665, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.674, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.724, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.716, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.780, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.665, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.674, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.724, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.781, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.663, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.887, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.887, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.888, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.887, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.865, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1269.406, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1008.238, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-1265.963, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-973.068, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-897.970, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1269.405, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1008.234, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-1265.972, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-973.075, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-897.969, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1269.403, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1008.172, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-1266.013, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-973.144, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-897.973, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1269.406, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1008.238, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1265.963, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-973.067, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-897.970, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1269.775, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1007.675, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-1266.515, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-973.204, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-898.107, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.676, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.723, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.720, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.779, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.674, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.675, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.723, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.720, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.779, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.674, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.676, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.722, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.720, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.778, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.674, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.676, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.723, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.720, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.779, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.674, total= 1.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.677, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.720, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.778, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.677, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.860, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1399.557, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1107.298, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-1217.735, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-938.531, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-886.021, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1399.551, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1107.300, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-1217.734, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-938.543, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-886.019, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1399.510, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1107.297, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-1217.723, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-938.649, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-886.005, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1399.558, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1107.298, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1217.735, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-938.530, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-886.021, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1406.744, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1109.116, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-1217.625, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-939.974, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-885.954, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.675, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.723, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.721, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.779, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.674, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.675, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.722, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.779, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.674, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.676, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.722, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.720, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.778, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.674, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.675, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.723, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.721, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.779, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.674, total= 1.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.722, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.720, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.778, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.677, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.891, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1410.165, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-967.613, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1272.155, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-961.285, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-1065.272, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1410.170, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-967.612, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1272.159, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-961.303, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-1065.275, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1410.180, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-967.600, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1272.134, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-961.472, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-1065.287, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1410.165, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-967.613, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1272.156, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-961.283, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1065.273, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1417.436, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-967.802, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1271.938, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-962.958, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-1063.000, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.687, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.721, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.776, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.677, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.687, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.776, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.677, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.686, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.776, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.677, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.687, total= 0.7s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.721, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.776, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.677, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.686, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.715, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.776, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.903, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.905, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1613.585, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1013.712, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1217.214, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1257.777, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-1011.130, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1613.584, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1013.711, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1217.213, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1257.778, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-1011.113, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1613.634, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1013.707, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1217.200, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1257.752, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-1010.963, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1613.586, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1013.712, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1217.214, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1257.776, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-1011.131, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1614.317, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1013.567, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1216.974, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1257.315, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-1011.489, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.687, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.721, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.776, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.677, total= 0.5s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.687, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.776, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.677, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.687, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.721, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.776, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.678, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.687, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.721, total= 0.3s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.776, total= 0.4s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.677, total= 0.6s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.688, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.718, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.776, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.2s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.904, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1435.387, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-875.495, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1190.152, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-920.197, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-1014.669, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1435.388, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-875.494, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1190.152, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-920.206, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-1014.660, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1435.406, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-875.486, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1190.160, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-920.297, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-1014.501, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1435.387, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-875.495, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1190.152, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-920.196, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-1014.671, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1436.397, total= 0.1s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-875.208, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1190.078, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-920.828, total= 0.0s [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=100, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-1014.415, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.099, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.098, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.098, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.148, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.099, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.260, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.095, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.276, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.136, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.259, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5405.743, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3631.151, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4909.685, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4823.292, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3729.075, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5405.752, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3631.151, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4909.677, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4823.302, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3729.077, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5405.827, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3631.142, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4909.443, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4823.589, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3729.082, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5405.742, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3631.151, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4909.685, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4823.288, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3729.074, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-5406.412, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-3630.477, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-4909.519, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-4828.358, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-3729.648, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.099, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.147, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.098, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.096, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.148, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.099, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.147, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.147, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.099, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.284, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.260, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.148, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-6221.944, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3821.922, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4800.744, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4153.231, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-6221.927, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3821.912, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4800.740, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4153.233, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-6221.761, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3821.796, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4800.651, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4153.357, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3664.392, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-6221.945, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3821.923, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4800.746, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4153.231, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-6217.538, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-3821.289, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-4799.749, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-4153.291, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-3664.207, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.093, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.261, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.093, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.096, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.273, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.146, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.261, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.145, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.093, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.099, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.276, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.139, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.258, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.150, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-5399.209, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-3631.534, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-4909.963, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-4823.378, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-3729.016, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-5399.202, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-3631.539, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-4909.956, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-4823.392, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-3729.017, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-5399.202, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-3631.593, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-4909.850, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-4823.724, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-3729.037, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5399.209, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3631.532, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4909.964, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4823.376, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3729.016, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-5398.789, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-3632.415, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-4909.952, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-4824.912, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-3729.338, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.9s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.9s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.093, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.261, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.145, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.093, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.274, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.261, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.097, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.272, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.262, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.093, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.274, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.145, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.101, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.275, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.136, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.149, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-6213.940, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-3822.154, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-4801.021, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-4161.559, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-3634.601, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-6213.945, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-3822.144, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-4801.017, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-4161.574, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-3634.606, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-6213.983, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-3822.114, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-4800.941, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-4161.644, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-3634.613, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-6213.940, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3822.155, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4801.021, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4161.558, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3634.601, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-6214.065, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-3821.379, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-4800.345, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-4162.714, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-3634.479, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.089, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.280, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.254, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.089, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.280, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.254, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.089, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.279, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.139, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.255, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.089, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.279, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.255, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.086, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.278, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.256, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.905, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-5398.955, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-3633.221, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-4908.447, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-5210.514, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-3728.627, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-5398.954, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-3633.212, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-4908.437, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-5210.507, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-3728.619, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-5398.949, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-3633.082, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-4908.352, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-5210.452, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-3728.539, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5398.954, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3633.223, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4908.448, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5210.516, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3728.627, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-5399.292, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-3489.473, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-4907.913, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-5209.187, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-3728.263, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.9s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.089, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.279, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.255, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.089, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.279, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.255, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.088, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.278, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.139, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.256, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.089, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.279, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.141, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.255, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.086, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.277, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.131, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.256, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.138, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.862, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.862, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-5499.416, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-3434.813, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-4799.525, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-4066.828, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-3786.685, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-5499.417, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-3434.814, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-4799.511, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-4066.829, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-3786.682, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-5499.478, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-3434.805, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-4799.423, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-4066.808, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-3786.662, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-5499.416, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3434.814, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4799.527, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4066.827, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3786.686, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-5499.406, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-3434.970, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-4798.636, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-4088.149, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-3786.549, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.072, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.134, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.254, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.151, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.072, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.134, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.254, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.151, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.073, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.285, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.136, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.253, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.151, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.072, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.134, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.254, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.151, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.079, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.285, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.134, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.150, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5412.862, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4906.904, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5923.728, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3713.471, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5412.863, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4906.899, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5923.745, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3713.472, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5412.783, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3632.378, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4906.757, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5923.960, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3713.478, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5412.862, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4906.904, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5923.727, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3713.471, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-5420.581, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-3632.574, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-4905.938, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-5925.995, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-3713.460, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 1.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.8s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.6s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.072, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.134, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.254, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.151, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.072, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.254, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.151, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.073, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.286, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.136, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.253, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.150, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.072, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.254, total= 0.7s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.151, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.082, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.291, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.133, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.252, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.152, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.2s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.3s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-5441.404, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3605.619, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4798.004, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3974.831, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3715.764, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-5441.408, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3605.624, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4797.996, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3974.830, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3715.762, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-5441.450, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3605.726, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4797.960, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3974.850, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3715.720, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-5441.403, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3605.618, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4798.005, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3974.831, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3715.764, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-5442.397, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3607.594, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-4798.292, total= 0.0s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3974.470, total= 0.1s [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3715.221, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.673, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.721, total= 1.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.765, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.666, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.673, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.721, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.765, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.666, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.673, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.723, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.766, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.666, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.673, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.722, total= 2.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 2.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.765, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.666, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.662, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.722, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.710, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.767, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.667, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5405.743, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3631.151, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4909.685, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4823.292, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3729.075, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5405.752, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3631.151, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4909.677, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4823.302, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3729.077, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5405.827, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3631.142, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4909.443, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4823.589, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3729.082, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5405.742, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3631.151, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4909.685, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4823.288, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3729.074, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-5406.412, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-3630.477, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-4909.519, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-4828.358, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-3729.648, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.673, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.722, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.765, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.667, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.673, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.722, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.765, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.666, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.672, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.723, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.765, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.665, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.673, total= 1.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.722, total= 1.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 2.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.765, total= 2.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.667, total= 1.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.661, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.721, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.767, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.666, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-6221.944, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3821.922, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4800.744, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4153.231, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-6221.927, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3821.912, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4800.740, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4153.233, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-6221.761, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3821.796, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4800.651, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4153.357, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3664.392, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-6221.945, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3821.923, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4800.746, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4153.231, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3663.721, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-6217.538, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-3821.289, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-4799.749, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-4153.291, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-3664.207, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.754, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.722, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.767, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.663, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.722, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.767, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.663, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.672, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.722, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.767, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.664, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.722, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.767, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.663, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.666, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.721, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.711, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.766, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.667, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-5399.209, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-3631.534, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-4909.963, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-4823.378, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-3729.016, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-5399.202, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-3631.539, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-4909.956, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-4823.392, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-3729.017, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-5399.202, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-3631.593, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-4909.850, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-4823.724, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-3729.037, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5399.209, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3631.532, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4909.964, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4823.376, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3729.016, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-5398.789, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-3632.415, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-4909.952, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-4824.912, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-3729.338, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.754, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.722, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.716, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.766, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.663, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.723, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.716, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.766, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.663, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.670, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.723, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.767, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.664, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 1.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.722, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.716, total= 1.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.766, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.663, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.667, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.724, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.711, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.764, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.671, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.867, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-6213.940, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-3822.154, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-4801.021, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-4161.559, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-3634.601, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-6213.945, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-3822.144, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-4801.017, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-4161.574, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-3634.606, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-6213.983, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-3822.114, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-4800.941, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-4161.644, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-3634.613, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-6213.940, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3822.155, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4801.021, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4161.558, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3634.601, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-6214.065, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-3821.379, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-4800.345, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-4162.714, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-3634.479, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.670, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.719, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.710, total= 1.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.768, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.671, total= 1.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.670, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.719, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.711, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.769, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.671, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.667, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.718, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.711, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.769, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.670, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.670, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.719, total= 1.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.710, total= 1.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.768, total= 1.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.671, total= 2.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.664, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.770, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.674, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.905, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-5398.955, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-3633.221, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-4908.447, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-5210.514, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-3728.627, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-5398.954, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-3633.212, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-4908.437, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-5210.507, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-3728.619, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-5398.949, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-3633.082, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-4908.352, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-5210.452, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-3728.539, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5398.954, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3633.223, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4908.448, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5210.516, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3728.627, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-5399.292, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-3489.473, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-4907.913, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-5209.187, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-3728.263, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.669, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.719, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.710, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.768, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.671, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.669, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.719, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.711, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.768, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.671, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.667, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.718, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.711, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.770, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.671, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.669, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.719, total= 1.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.710, total= 1.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.768, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.671, total= 2.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.668, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.717, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.769, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.673, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.862, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.862, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.898, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-5499.416, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-3434.813, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-4799.525, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-4066.828, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-3786.685, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-5499.417, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-3434.814, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-4799.511, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-4066.829, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-3786.682, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-5499.478, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-3434.805, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-4799.423, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-4066.808, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-3786.662, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-5499.416, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3434.814, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4799.527, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4066.827, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3786.686, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-5499.406, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-3434.970, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-4798.636, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-4088.149, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-3786.549, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.675, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.769, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.673, total= 1.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.675, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.769, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.673, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.672, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.718, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.770, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.671, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.675, total= 2.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 1.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.769, total= 1.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.673, total= 1.8s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.680, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.717, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.711, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.769, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.673, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.863, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.863, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.899, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5412.862, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-4906.904, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-5923.728, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-3713.471, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5412.863, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-4906.899, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-5923.745, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-3713.472, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5412.783, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3632.378, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-4906.757, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-5923.960, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-3713.478, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5412.862, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3632.385, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-4906.904, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-5923.727, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-3713.471, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-5420.581, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-3632.574, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-4905.938, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-5925.995, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-3713.460, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 0.7s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.5s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.675, total= 1.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.769, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.673, total= 0.8s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.676, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.718, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.769, total= 0.6s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.673, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.673, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.719, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.769, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.671, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.675, total= 1.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.769, total= 0.9s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.673, total= 1.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.678, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.720, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.709, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.770, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.671, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.864, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.864, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.3s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.2s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-5441.404, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3605.619, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-4798.004, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3974.831, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-3715.764, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-5441.408, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3605.624, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-4797.996, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3974.830, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-3715.762, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-5441.450, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3605.726, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-4797.960, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3974.850, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-3715.720, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-5441.403, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3605.618, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-4798.005, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3974.831, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-3715.764, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-5442.397, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3607.594, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-4798.292, total= 0.1s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3974.470, total= 0.0s [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=200, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-3715.221, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 2.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 2.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.097, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.281, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.258, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.147, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.097, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.282, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.258, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.147, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.097, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.282, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.146, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.258, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.097, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.281, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.258, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.147, total= 3.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.099, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.274, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.145, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.860, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.907, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.907, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.860, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.907, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-19103.246, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10339.782, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-15051.433, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11297.026, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11634.290, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-19103.244, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10339.782, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-15051.432, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11297.038, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11634.295, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-19103.377, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10339.722, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-15051.482, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11297.246, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11634.374, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19103.246, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10339.782, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15051.434, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11297.025, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11634.289, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-19103.751, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-10337.434, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-15051.523, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11300.629, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11634.600, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.097, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.282, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.258, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.147, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.097, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.282, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.258, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.147, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.096, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.282, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.258, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.097, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.281, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.258, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.147, total= 2.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.099, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.273, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.132, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.260, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.860, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.907, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.860, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.907, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.860, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.907, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-19355.689, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14830.431, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14715.696, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-12180.627, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11217.931, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-19355.697, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14830.441, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14715.692, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-12180.632, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11217.937, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-19355.794, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14830.551, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14715.612, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-12180.605, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11217.969, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19355.688, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14830.431, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14715.697, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12180.627, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11217.931, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-19354.998, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-14831.734, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-14715.485, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-12180.083, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11218.128, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.103, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.261, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.103, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.102, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.279, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.139, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.261, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.103, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.279, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.102, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.276, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.130, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.261, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.147, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.894, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-19103.304, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-10340.012, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-15051.850, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-11165.326, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-11573.753, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-19103.306, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-10340.014, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-15051.851, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-11165.364, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-11573.766, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-19103.351, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-10339.960, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-15051.801, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-11165.664, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-11573.845, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19103.304, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10340.013, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15051.849, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11165.322, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11573.753, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-19103.117, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10339.319, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-15052.100, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-11169.801, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-11574.563, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.103, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.278, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.261, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.145, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.103, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.261, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.102, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.279, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.261, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.103, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.279, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.145, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.100, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.277, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.133, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.266, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.860, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-19361.711, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-14830.346, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-14716.112, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-12187.435, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-11217.860, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-19361.728, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-14830.354, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-14716.123, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-12187.439, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-11217.858, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-19361.791, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-14830.409, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-14716.034, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-12187.456, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-11217.927, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19361.713, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14830.345, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14716.113, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12187.435, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11217.861, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-19357.319, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-14831.545, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-14715.922, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-12186.844, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-11218.244, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.093, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.256, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.143, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.093, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.257, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.094, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.139, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.141, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.093, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.256, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.143, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.091, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.277, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.142, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.255, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.147, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.862, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.910, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.907, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.862, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.910, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.862, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.908, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.862, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.910, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.907, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.908, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-18909.773, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11329.200, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-15049.592, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11628.883, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11207.546, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-18909.778, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11329.199, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-15049.582, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11628.878, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11207.553, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-18909.797, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11329.146, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-15049.503, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11628.887, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11207.578, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-18909.772, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11329.201, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15049.593, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11628.883, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11207.545, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-18910.474, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11328.512, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-15048.729, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11628.942, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11208.191, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.093, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.256, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.093, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.257, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.094, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.282, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.139, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.257, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.140, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.093, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 1.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.256, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.143, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.095, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.280, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.254, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.862, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.908, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.862, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.908, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.862, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.908, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.862, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.908, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.861, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-19362.875, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-11706.989, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-14713.848, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-12182.444, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-11031.687, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-19362.871, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-11706.997, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-14713.844, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-12182.438, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-11031.691, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-19362.886, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-11707.192, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-14713.816, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-12182.336, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-11031.805, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19362.875, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11706.986, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14713.849, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12182.444, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11031.686, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-19363.640, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-11707.389, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-14713.311, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-12183.000, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-11032.714, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 1.6s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.6s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.076, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.283, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.135, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.252, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.077, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.283, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.252, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.076, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.284, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.134, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.253, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.152, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.076, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.282, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.135, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.252, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.081, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.290, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.138, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.252, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.153, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.914, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.914, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.5s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.874, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-19102.693, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11927.603, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-15047.292, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11641.473, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11278.115, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-19102.695, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11927.617, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-15047.303, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11641.452, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11278.110, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-19102.688, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11927.753, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-15047.280, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11641.337, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11278.145, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19102.693, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11927.602, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15047.293, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11641.475, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11278.114, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-19102.736, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11929.038, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-15045.621, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11638.757, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11277.957, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.5s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 2.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.8s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.076, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.283, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.135, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.252, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.077, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.283, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.075, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.283, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.135, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.252, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.152, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.076, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.283, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.252, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.076, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.284, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.136, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.252, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.151, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.4s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.914, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.873, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-19364.063, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9825.256, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14711.541, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-12183.673, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10955.977, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-19364.052, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9825.286, total= 0.0s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14711.538, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-12183.672, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10955.946, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-19364.021, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9825.532, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14711.521, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-12183.631, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10955.766, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19364.063, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9825.251, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14711.541, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12183.673, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10955.979, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-19362.500, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-9828.075, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-14712.309, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-12183.024, total= 0.1s [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-10950.980, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.662, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.719, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.712, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.763, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.659, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.662, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.719, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.712, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.762, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.659, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.661, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.719, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.712, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.763, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.660, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.662, total= 4.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.719, total= 1.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.712, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.763, total= 2.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.659, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.653, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.706, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.762, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.663, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.860, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.907, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.902, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.860, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.907, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.901, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-19103.246, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-10339.782, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-15051.433, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11297.026, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11634.290, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-19103.244, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-10339.782, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-15051.432, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11297.038, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11634.295, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-19103.377, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-10339.722, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-15051.482, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11297.246, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11634.374, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19103.246, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10339.782, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15051.434, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11297.025, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11634.289, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-19103.751, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-10337.434, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-15051.523, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11300.629, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-11634.600, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.662, total= 2.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.720, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.712, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.762, total= 2.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.659, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.662, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.720, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.712, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.762, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.659, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.661, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.719, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.712, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.762, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.660, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.662, total= 2.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.720, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.712, total= 2.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.762, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.659, total= 1.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.651, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.715, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.706, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.762, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.667, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.860, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.907, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.902, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.902, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.860, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.902, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.860, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.907, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.902, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.867, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-19355.689, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14830.431, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14715.696, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-12180.627, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-11217.931, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-19355.697, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14830.441, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14715.692, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-12180.632, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-11217.937, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-19355.794, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14830.551, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14715.612, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-12180.605, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-11217.969, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19355.688, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14830.431, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14715.697, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12180.627, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11217.931, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-19354.998, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-14831.734, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-14715.485, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-12180.083, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-11218.128, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.661, total= 1.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.721, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.763, total= 1.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.654, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.660, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.721, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.712, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.763, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.654, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.660, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.721, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.762, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.655, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.661, total= 2.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.721, total= 2.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 2.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.763, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.654, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.657, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.716, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.706, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.761, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.660, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.894, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.894, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.859, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.894, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.859, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.894, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.858, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-19103.304, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-10340.012, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-15051.850, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-11165.326, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-11573.753, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-19103.306, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-10340.014, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-15051.851, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-11165.364, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-11573.766, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-19103.351, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-10339.960, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-15051.801, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-11165.664, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-11573.845, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19103.304, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-10340.013, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15051.849, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11165.322, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11573.753, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-19103.117, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-10339.319, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-15052.100, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-11169.801, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-11574.563, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.661, total= 2.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.721, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 2.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.762, total= 2.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.654, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.661, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.721, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.713, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.763, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.654, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.660, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.722, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.712, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.762, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.655, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.661, total= 2.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.721, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 3.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.762, total= 2.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.654, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.653, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.718, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.708, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.764, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.660, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.895, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.859, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.859, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.895, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.859, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.895, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.860, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-19361.711, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-14830.346, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-14716.112, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-12187.435, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-11217.860, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-19361.728, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-14830.354, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-14716.123, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-12187.439, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-11217.858, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-19361.791, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-14830.409, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-14716.034, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-12187.456, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-11217.927, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19361.713, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14830.345, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14716.113, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12187.435, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11217.861, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-19357.319, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-14831.545, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-14715.922, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-12186.844, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-11218.244, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.662, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.719, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.706, total= 1.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.766, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.668, total= 1.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.662, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.719, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.706, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.766, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.668, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.662, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.719, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.706, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.767, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.668, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.662, total= 4.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.719, total= 2.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.706, total= 3.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.766, total= 7.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.667, total= 3.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.660, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.767, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.674, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.862, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.910, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.907, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.862, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.910, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.907, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.862, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.908, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.862, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.910, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.907, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.862, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.908, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-18909.773, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11329.200, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-15049.592, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11628.883, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-11207.546, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-18909.778, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11329.199, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-15049.582, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11628.878, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-11207.553, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-18909.797, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11329.146, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-15049.503, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11628.887, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-11207.578, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-18909.772, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11329.201, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15049.593, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11628.883, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11207.545, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-18910.474, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11328.512, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-15048.729, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11628.942, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-11208.191, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.662, total= 2.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.719, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.706, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.766, total= 1.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.667, total= 2.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.662, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.719, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.706, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.766, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.668, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.661, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.719, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.706, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.766, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.668, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.662, total= 4.7s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.719, total= 2.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.706, total= 3.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.766, total= 2.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.667, total= 3.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.658, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.715, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.708, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.767, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.862, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.908, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.862, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.908, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.862, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.908, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.862, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.908, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.861, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.897, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-19362.875, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-11706.989, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-14713.848, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-12182.444, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-11031.687, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-19362.871, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-11706.997, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-14713.844, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-12182.438, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-11031.691, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-19362.886, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-11707.192, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-14713.816, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-12182.336, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-11031.805, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19362.875, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11706.986, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14713.849, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12182.444, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-11031.686, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-19363.640, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-11707.389, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-14713.311, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-12183.000, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-11032.714, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.662, total= 1.5s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.716, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.712, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.764, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.668, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.663, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.712, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.764, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.668, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.663, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.715, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.765, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.669, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.662, total= 2.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.716, total= 1.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.712, total= 1.5s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.764, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.668, total= 3.5s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.662, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.715, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.711, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.767, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.669, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.874, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-19102.693, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11927.603, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-15047.292, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11641.473, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-11278.115, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-19102.695, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11927.617, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-15047.303, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11641.452, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-11278.110, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-19102.688, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11927.753, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-15047.280, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11641.337, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-11278.145, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-19102.693, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11927.602, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-15047.293, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11641.475, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-11278.114, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-19102.736, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11929.038, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-15045.621, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11638.757, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-11277.957, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 1.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.662, total= 1.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.712, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.764, total= 2.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.668, total= 1.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.663, total= 0.7s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 0.6s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.712, total= 0.5s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.764, total= 1.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.668, total= 0.8s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.663, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.715, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.712, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.765, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.669, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.662, total= 2.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.712, total= 1.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.764, total= 2.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.668, total= 2.9s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.663, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.711, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.766, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.670, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.899, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.867, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.914, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.914, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.867, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.914, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.899, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 0.3s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.4s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.914, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.873, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-19364.063, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-9825.256, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-14711.541, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-12183.673, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-10955.977, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-19364.052, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-9825.286, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-14711.538, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-12183.672, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-10955.946, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-19364.021, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-9825.532, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-14711.521, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-12183.631, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-10955.766, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-19364.063, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-9825.251, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-14711.541, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-12183.673, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-10955.979, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-19362.500, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-9828.075, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-14712.309, total= 0.1s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-12183.024, total= 0.0s [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=350, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-10950.980, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.280, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.143, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.280, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.280, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.143, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.100, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.272, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.254, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.143, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.905, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-35380.480, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-32048.167, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-30710.485, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-29034.391, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-25542.330, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-35380.486, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-32048.167, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-30710.489, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-29034.393, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-25542.321, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-35380.430, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-32048.117, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-30710.369, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-29034.163, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-25542.284, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-35380.478, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32048.166, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30710.485, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29034.394, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-25542.331, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-35381.258, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-32050.178, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-30709.596, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-29030.504, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-25541.831, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.281, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.101, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.099, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.280, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.258, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.101, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.281, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.258, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.095, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.271, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.131, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.256, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.905, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-36455.653, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-31459.615, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-30027.123, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-25062.322, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-26418.396, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-36455.641, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-31459.620, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-30027.120, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-25062.316, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-26418.371, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-36455.537, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-31459.624, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-30026.979, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-25062.237, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-26417.882, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36455.655, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-31459.616, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30027.124, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25062.321, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-26418.402, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-36454.922, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-31458.363, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-30025.484, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-25062.978, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-26415.185, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.106, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.261, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.145, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.106, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.105, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.145, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.261, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.106, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.278, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.145, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.100, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.272, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.259, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.148, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.889, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.889, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.905, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.889, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.889, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-35380.524, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-32047.884, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-30711.075, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-29560.387, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-25542.370, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-35380.529, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-32047.882, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-30711.081, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-29560.358, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-25542.367, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-35380.623, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-32047.844, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-30710.961, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-29560.132, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-25542.387, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-35380.523, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32047.884, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30711.075, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29560.391, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-25542.371, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-35381.338, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-32047.772, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-30710.221, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-29558.487, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-25543.003, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.106, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.278, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.261, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.145, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.107, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.277, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.261, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.107, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.284, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.261, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.106, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.278, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.145, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.105, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.274, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.133, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.256, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.905, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.905, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-39768.979, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-31459.402, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-30027.716, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-25062.796, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-26417.425, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-39768.988, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-31459.392, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-30027.706, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-25062.784, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-26417.498, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-39769.101, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-31459.365, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-30027.601, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-25062.681, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-26418.107, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-39768.979, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-31459.401, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30027.717, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25062.796, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-26417.417, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-39769.827, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-31458.078, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-30028.698, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-25063.463, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-26417.046, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 2.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.093, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.256, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.093, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.282, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.256, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.093, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.282, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.139, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.093, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.256, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.143, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.095, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.281, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.137, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.259, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.140, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.857, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.892, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.857, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.857, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.857, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.892, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-34875.917, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-32050.429, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-30707.858, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-29031.066, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-24000.967, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-34875.927, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-32050.494, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-30707.840, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-29031.074, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-24000.973, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-34876.291, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-32051.212, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-30707.881, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-29031.084, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-24001.054, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-34875.916, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32050.424, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30707.860, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29031.066, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-24000.965, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-34879.359, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-32057.388, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-30708.825, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-29030.469, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-24001.889, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 1.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.093, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.256, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.093, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.282, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.256, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.093, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.281, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.140, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.257, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.093, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.282, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.256, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.143, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.094, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.279, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.140, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.259, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.145, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.857, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.892, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.857, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.893, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.857, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.892, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.892, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-36457.597, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-22737.184, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-30024.488, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-24677.298, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-36457.596, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-22737.195, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-30024.480, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-24677.298, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-36457.530, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-22737.280, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-30024.432, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-24677.263, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-23908.108, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36457.596, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-22737.184, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30024.489, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-24677.299, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-36456.471, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-22737.004, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-30024.125, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-24676.737, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-23908.298, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.080, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.135, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.252, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.080, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.252, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.081, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.135, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.252, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.151, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.080, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.135, total= 0.6s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.252, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.088, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.286, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.255, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.150, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.915, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.915, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.915, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.915, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.915, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-34200.517, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-22772.647, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-30704.581, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-29016.738, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-23995.055, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-34200.524, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-22772.494, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-30704.583, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-29016.717, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-23995.059, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-34200.606, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-22771.263, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-30704.452, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-29016.707, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-23995.086, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-34200.515, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-22772.660, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30704.581, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29016.736, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-23995.059, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-34200.816, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-22763.306, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-30703.620, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-29017.610, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-23995.650, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.8s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.9s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.6s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 2.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.080, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.135, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.252, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.080, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.081, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.284, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.135, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.252, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.151, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.080, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.7s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.252, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.082, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.288, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.136, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.250, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.155, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.915, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.915, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.915, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.861, total= 0.3s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.915, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 0.5s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.914, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-36460.036, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-21823.052, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-30021.196, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-25057.618, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-23895.990, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-36460.046, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-21823.055, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-30021.191, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-25057.620, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-23896.009, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-36460.084, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-21823.076, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-30021.154, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-25057.687, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-23896.224, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36460.034, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-21823.052, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30021.197, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25057.618, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-23895.988, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-36460.024, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-21823.136, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-30019.744, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-25058.146, total= 0.0s [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-23898.793, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.655, total= 3.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.716, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.709, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.755, total= 3.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.655, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.655, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.709, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.755, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.655, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.656, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.708, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.657, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.655, total= 7.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.716, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.709, total= 2.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.755, total= 4.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.655, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.652, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.705, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.758, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.661, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.905, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-35380.480, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-32048.167, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-30710.485, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-29034.391, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-25542.330, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-35380.486, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-32048.167, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-30710.489, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-29034.393, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-25542.321, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-35380.430, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-32048.117, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-30710.369, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-29034.163, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-25542.284, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-35380.478, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32048.166, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30710.485, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29034.394, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-25542.331, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-35381.258, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-32050.178, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-30709.596, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-29030.504, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-25541.831, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.655, total= 3.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.717, total= 2.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.709, total= 2.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.755, total= 3.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.655, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.655, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.716, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.709, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.755, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.655, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.654, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.709, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.754, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.652, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.655, total= 8.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.717, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.709, total= 2.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.755, total= 8.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.655, total= 2.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.644, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.703, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.755, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.663, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.906, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.906, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.906, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.906, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.905, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.866, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-36455.653, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-31459.615, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-30027.123, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-25062.322, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-26418.396, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-36455.641, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-31459.620, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-30027.120, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-25062.316, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-26418.371, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-36455.537, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-31459.624, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-30026.979, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-25062.237, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-26417.882, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36455.655, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-31459.616, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30027.124, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25062.321, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-26418.402, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-36454.922, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-31458.363, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-30025.484, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-25062.978, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-26415.185, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.655, total= 4.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.705, total= 4.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.757, total= 2.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.653, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.654, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.706, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.757, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.653, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.654, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.709, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.650, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.655, total= 8.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 3.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.705, total= 5.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.757, total= 3.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.653, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.649, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.705, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.758, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.657, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.856, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.889, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.866, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.856, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.889, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.905, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.889, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.856, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.889, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.866, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.890, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.906, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-35380.524, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-32047.884, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-30711.075, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-29560.387, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-25542.370, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-35380.529, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-32047.882, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-30711.081, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-29560.358, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-25542.367, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-35380.623, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-32047.844, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-30710.961, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-29560.132, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-25542.387, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-35380.523, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32047.884, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30711.075, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29560.391, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-25542.371, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-35381.338, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-32047.772, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-30710.221, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-29558.487, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-25543.003, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.654, total= 2.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 2.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.705, total= 4.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.757, total= 3.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.653, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.654, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.718, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.706, total= 1.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.757, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.653, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.654, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.718, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.709, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.753, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.653, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.654, total= 6.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 4.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.706, total= 6.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.757, total= 4.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.653, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.649, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.707, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.753, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.660, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.856, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.866, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.856, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.905, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.905, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.866, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.905, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.905, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.866, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.856, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.905, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.905, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.866, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.853, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.891, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.907, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.868, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-39768.979, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-31459.402, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-30027.716, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-25062.796, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-26417.425, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-39768.988, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-31459.392, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-30027.706, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-25062.784, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-26417.498, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-39769.101, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-31459.365, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-30027.601, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-25062.681, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-26418.107, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-39768.979, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-31459.401, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30027.717, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25062.796, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-26417.417, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-39769.827, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-31458.078, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-30028.698, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-25063.463, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-26417.046, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.658, total= 2.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 2.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.706, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.764, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.665, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.657, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.705, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.764, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.665, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.659, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.719, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.704, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.765, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.666, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.658, total= 5.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 7.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.706, total= 9.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.764, total= 3.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.665, total= 8.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.657, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.716, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.768, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.677, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.857, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.892, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.857, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.857, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.857, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.892, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.893, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-34875.917, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-32050.429, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-30707.858, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-29031.066, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-24000.967, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-34875.927, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-32050.494, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-30707.840, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-29031.074, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-24000.973, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-34876.291, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-32051.212, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-30707.881, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-29031.084, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-24001.054, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-34875.916, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-32050.424, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30707.860, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29031.066, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-24000.965, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-34879.359, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-32057.388, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-30708.825, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-29030.469, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-24001.889, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.658, total= 4.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 3.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.706, total= 1.9s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.764, total= 2.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.665, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.658, total= 1.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.718, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.706, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.764, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.665, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.660, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.720, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.705, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.764, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.665, total= 0.6s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.658, total= 6.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 4.8s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.705, total= 4.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.764, total= 4.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.665, total= 3.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.661, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.767, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.857, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.892, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.857, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.892, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.856, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.893, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.857, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.892, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.859, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.892, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-36457.597, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-22737.184, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-30024.488, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-24677.298, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-36457.596, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-22737.195, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-30024.480, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-24677.298, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-36457.530, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-22737.280, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-30024.432, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-24677.263, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-23908.108, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36457.596, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-22737.184, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30024.489, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-24677.299, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-23908.005, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-36456.471, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-22737.004, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-30024.125, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-24676.737, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-23908.298, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.811, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.658, total= 2.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 2.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.765, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.669, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.658, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.715, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.765, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.669, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.658, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.715, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.766, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.669, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.658, total= 3.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 7.6s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 1.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.765, total= 2.6s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.669, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.655, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.768, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.669, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.915, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.896, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.915, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.896, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.915, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.896, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.861, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.915, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.896, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.863, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.915, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.895, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-34200.517, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-22772.647, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-30704.581, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-29016.738, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-23995.055, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-34200.524, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-22772.494, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-30704.583, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-29016.717, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-23995.059, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-34200.606, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-22771.263, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-30704.452, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-29016.707, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-23995.086, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-34200.515, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-22772.660, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-30704.581, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-29016.736, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-23995.059, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-34200.816, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-22763.306, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-30703.620, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-29017.610, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-23995.650, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.6s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 1.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 0.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.811, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.658, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 3.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 1.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.765, total= 2.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.669, total= 1.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.658, total= 0.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 1.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.765, total= 1.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.669, total= 0.9s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.658, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.715, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.766, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.670, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.658, total= 3.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 9.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 2.7s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.765, total= 2.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.669, total= 2.8s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.654, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.714, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.767, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.861, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.915, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.861, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.915, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.861, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.915, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.861, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.915, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.3s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 0.5s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.864, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.914, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.896, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-36460.036, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-21823.052, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-30021.196, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-25057.618, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-23895.990, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-36460.046, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-21823.055, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-30021.191, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-25057.620, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-23896.009, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-36460.084, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-21823.076, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-30021.154, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-25057.687, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-23896.224, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-36460.034, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-21823.052, total= 0.1s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-30021.197, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-25057.618, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-23895.988, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-36460.024, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-21823.136, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-30019.744, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-25058.146, total= 0.0s [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=500, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-23898.793, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.102, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.281, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.257, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.102, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.281, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.257, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.101, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.279, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.102, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.281, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.257, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.099, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.279, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.132, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.149, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.849, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85570.222, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-72853.307, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.592, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-43502.770, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-52432.220, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85570.202, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-72853.282, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.629, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-43502.773, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-52432.205, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85570.017, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-72853.471, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.258, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-43502.613, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-52431.970, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85570.226, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72853.310, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.589, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-43502.770, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52432.222, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-85455.208, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-72854.167, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-72808.919, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-43502.794, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-52430.068, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.102, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.281, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.257, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.103, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.281, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.257, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.103, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.278, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.259, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.102, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.281, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.257, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.098, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.276, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.132, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.141, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.849, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-79501.702, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-68632.788, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-67561.742, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-62961.242, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-63712.461, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-79501.701, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-68632.777, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-67561.742, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-62961.195, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-63712.440, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-79501.724, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-68632.652, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-67561.752, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-62960.749, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-63712.132, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79501.702, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-68632.787, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67561.741, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62961.248, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63712.465, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-79501.633, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-68633.495, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-67561.658, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-62957.134, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-63710.451, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 2.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.110, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.280, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.261, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.110, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.280, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.110, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.284, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.261, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.110, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.280, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.106, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.268, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.260, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.146, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-85569.056, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-73861.307, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.543, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-47318.177, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-52432.032, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-85569.047, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-73861.326, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.651, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-47318.103, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-52432.021, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-85568.980, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-73861.654, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.400, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-47317.043, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-52431.790, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85569.059, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73861.303, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.526, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-47318.186, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52432.033, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-85454.276, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-73863.799, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-72808.905, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-47310.892, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-52429.815, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.110, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.280, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.260, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.110, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.280, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.260, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.108, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.260, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.110, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.280, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.106, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.271, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.127, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.143, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-79386.385, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-67392.830, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-67562.446, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-62961.578, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-55315.425, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-79386.349, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-67392.766, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-67562.437, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-62961.519, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-55315.402, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-79386.216, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-67392.535, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-67562.436, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-62961.154, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-55315.283, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79386.387, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67392.831, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67562.446, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62961.583, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-55315.424, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-79386.456, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-67388.332, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-67562.259, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-62955.764, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-55317.788, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 2.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.093, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 1.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.255, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.093, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.255, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.093, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.278, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.140, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.093, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.278, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.255, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.089, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.282, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.133, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.261, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.138, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.852, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.884, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.852, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.884, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.871, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.852, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.884, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-85575.418, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-72560.163, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.869, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-60793.452, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-52223.266, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-85575.412, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-72560.229, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.888, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-60793.451, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-52223.287, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-85575.265, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-72560.943, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.890, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-60793.335, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-52223.461, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85575.420, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72560.154, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.867, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60793.453, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52223.264, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-85575.124, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-72568.329, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-72810.017, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-60793.200, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-52224.845, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.093, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.278, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.255, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.093, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.255, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.093, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.277, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.140, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.256, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.142, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.093, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.278, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 2.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.255, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.097, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.279, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.131, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.255, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.143, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.852, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.904, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.885, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.852, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.904, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.904, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.871, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.852, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.904, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.885, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.905, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-79389.635, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-68493.307, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-67558.610, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-62959.754, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-63715.611, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-79389.618, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-68493.188, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-67558.617, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-62959.702, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-63715.587, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-79389.284, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-68492.335, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-67558.801, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-62959.381, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-63715.116, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79389.638, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-68493.316, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67558.610, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62959.760, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63715.616, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-79390.158, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-68479.916, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-67557.462, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-62954.968, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-63711.953, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 3.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.736, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.283, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.135, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.253, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.283, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.252, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.151, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.087, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.282, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.135, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.151, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.283, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.135, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.252, total= 0.8s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.088, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.286, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.150, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.885, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.7s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85581.928, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-54214.349, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-69078.009, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-60794.321, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-52434.116, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85581.930, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-54214.353, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-69078.009, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-60794.321, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-52434.133, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85581.766, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-54214.139, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-69077.889, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-60794.234, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-52434.273, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85581.929, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-54214.349, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-69078.008, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60794.322, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52434.115, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-85580.308, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-54212.336, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-69077.547, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-60794.258, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-52436.259, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 3.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.736, total= 0.9s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.283, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.135, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.252, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.283, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.151, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.088, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.282, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.134, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.151, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.092, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.283, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.252, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.5s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.093, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.292, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.134, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.150, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.886, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.886, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.3s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.886, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.886, total= 0.6s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-79086.080, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-48962.816, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-67554.696, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-62957.895, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-63922.023, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-79086.125, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-48962.774, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-67554.711, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-62957.860, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-63921.998, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-79086.628, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-48962.428, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-67554.706, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-62957.221, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-63922.142, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79086.080, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-48962.819, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67554.698, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62957.902, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63922.026, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-79389.800, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-48957.662, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-67556.623, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-62954.709, total= 0.0s [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-63925.502, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.651, total= 2.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 3.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.702, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.750, total= 2.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.651, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.651, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.703, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.751, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.651, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.650, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.702, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.654, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.651, total= 4.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 4.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.702, total= 4.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.750, total= 4.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.651, total= 3.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.643, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.754, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.657, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.900, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.849, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85570.222, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-72853.307, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.592, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-43502.770, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-52432.220, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85570.202, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-72853.282, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.629, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-43502.773, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-52432.205, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85570.017, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-72853.471, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.258, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-43502.613, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-52431.970, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85570.226, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72853.310, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.589, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-43502.770, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52432.222, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-85455.208, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-72854.167, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-72808.919, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-43502.794, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-52430.068, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 3.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 2.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.702, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.750, total= 3.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.651, total= 2.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.651, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.702, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.750, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.652, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.649, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.703, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.751, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.652, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 3.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 5.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.702, total= 3.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.750, total= 5.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.651, total= 4.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.643, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.718, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.707, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.755, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.663, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.900, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.900, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.900, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.849, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-79501.702, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-68632.788, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-67561.742, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-62961.242, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-63712.461, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-79501.701, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-68632.777, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-67561.742, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-62961.195, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-63712.440, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-79501.724, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-68632.652, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-67561.752, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-62960.749, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-63712.132, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79501.702, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-68632.787, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67561.741, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62961.248, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63712.465, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-79501.633, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-68633.495, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-67561.658, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-62957.134, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-63710.451, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.650, total= 4.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 5.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.704, total= 4.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.751, total= 6.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.648, total= 2.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.651, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.715, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.704, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.751, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.648, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.652, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.705, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.648, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.650, total= 8.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 6.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.704, total= 3.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.751, total= 5.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.648, total= 3.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.651, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.748, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.650, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.869, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.869, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.869, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.869, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-85569.056, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-73861.307, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.543, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-47318.177, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-52432.032, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-85569.047, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-73861.326, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.651, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-47318.103, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-52432.021, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-85568.980, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-73861.654, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.400, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-47317.043, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-52431.790, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85569.059, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-73861.303, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.526, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-47318.186, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52432.033, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-85454.276, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-73863.799, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-72808.905, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-47310.892, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-52429.815, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 2.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 2.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 3.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.704, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.751, total= 4.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.648, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.651, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.704, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.751, total= 2.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.648, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.651, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.716, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.704, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.751, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.646, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 4.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 7.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.704, total= 3.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.751, total= 7.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.648, total= 3.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.651, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.719, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.707, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.754, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.654, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.869, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.898, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.869, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.869, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-79386.385, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-67392.830, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-67562.446, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-62961.578, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-55315.425, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-79386.349, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-67392.766, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-67562.437, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-62961.519, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-55315.402, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-79386.216, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-67392.535, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-67562.436, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-62961.154, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-55315.283, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79386.387, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67392.831, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67562.446, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62961.583, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-55315.424, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-79386.456, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-67388.332, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-67562.259, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-62955.764, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-55317.788, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.807, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.653, total= 3.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.717, total= 6.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.707, total= 2.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.762, total= 5.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.660, total= 2.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.653, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.707, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.762, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.660, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.654, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.707, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.763, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.661, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.653, total= 5.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.717, total= 6.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.707, total= 4.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.762, total= 2.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.660, total= 3.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.641, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.717, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.764, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.674, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.852, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.904, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.884, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.852, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.904, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.884, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.904, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.871, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.852, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.904, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.884, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.854, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.904, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-85575.418, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-72560.163, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-72802.869, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-60793.452, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-52223.266, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-85575.412, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-72560.229, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-72802.888, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-60793.451, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-52223.287, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-85575.265, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-72560.943, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-72803.890, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-60793.335, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-52223.461, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85575.420, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72560.154, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-72802.867, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60793.453, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52223.264, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-85575.124, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-72568.329, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-72810.017, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-60793.200, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-52224.845, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.807, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.653, total= 4.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.717, total= 5.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.707, total= 2.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.762, total= 3.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.660, total= 2.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.653, total= 2.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.717, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.707, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.761, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.660, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.651, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.706, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.764, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.662, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.653, total= 7.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.717, total= 10.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.707, total= 3.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.762, total= 5.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.660, total= 3.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.646, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.762, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.675, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.852, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.904, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.885, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.852, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.904, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.885, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.904, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.871, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.852, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.904, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.885, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.905, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-79389.635, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-68493.307, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-67558.610, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-62959.754, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-63715.611, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-79389.618, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-68493.188, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-67558.617, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-62959.702, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-63715.587, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-79389.284, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-68492.335, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-67558.801, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-62959.381, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-63715.116, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79389.638, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-68493.316, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67558.610, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62959.760, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63715.616, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-79390.158, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-68479.916, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-67557.462, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-62954.968, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-63711.953, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.730, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 3.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.736, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.645, total= 2.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 3.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.761, total= 3.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.667, total= 2.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.645, total= 1.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.761, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.667, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.647, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.761, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.669, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.645, total= 3.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 3.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 5.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.761, total= 6.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.667, total= 3.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.641, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.765, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.673, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.885, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.885, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.885, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.885, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-85581.928, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-54214.349, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-69078.009, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-60794.321, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-52434.116, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-85581.930, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-54214.353, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-69078.009, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-60794.321, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-52434.133, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-85581.766, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-54214.139, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-69077.889, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-60794.234, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-52434.273, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-85581.929, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-54214.349, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-69078.008, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-60794.322, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-52434.115, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-85580.308, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-54212.336, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-69077.547, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-60794.258, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-52436.259, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.730, total= 1.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 3.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.736, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.644, total= 3.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 1.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.761, total= 3.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.667, total= 2.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.645, total= 2.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.760, total= 1.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.667, total= 1.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.646, total= 1.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.7s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.9s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.761, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.667, total= 0.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.644, total= 5.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 2.8s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 14.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.761, total= 10.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.667, total= 6.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.639, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.763, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.673, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.886, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.886, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.886, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.4s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.886, total= 0.6s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.5s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.856, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.886, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-79086.080, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-48962.816, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-67554.696, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-62957.895, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-63922.023, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-79086.125, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-48962.774, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-67554.711, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-62957.860, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-63921.998, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-79086.628, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-48962.428, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-67554.706, total= 0.1s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-62957.221, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-63922.142, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-79086.080, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-48962.819, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-67554.698, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-62957.902, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-63922.026, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-79389.800, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-48957.662, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-67556.623, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-62954.709, total= 0.0s [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=750, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-63925.502, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 3.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 2.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.102, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.281, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.257, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.102, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.281, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.257, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.103, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.280, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.102, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.281, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.257, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 4.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.103, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.276, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.255, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.143, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.910, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.910, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.910, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-88748.180, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-82599.199, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-82834.901, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-79474.812, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-59656.559, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-88748.243, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-82599.303, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-82834.920, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-79474.841, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-59656.540, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-88748.614, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-82599.950, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-82836.739, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-79475.220, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-59656.381, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88748.176, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82599.190, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82834.894, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-79474.810, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59656.561, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-88751.726, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-82607.590, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-82836.446, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-79475.239, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-59654.376, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 2.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 3.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.102, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.281, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.257, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.102, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.281, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.147, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.257, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.105, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.279, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.145, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.256, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.102, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.281, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.257, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.102, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.273, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.133, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.254, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.140, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.702, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-77275.021, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-76871.116, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71638.131, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-72450.092, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.696, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-77275.013, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-76871.142, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71638.083, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-72450.116, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.610, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-77274.941, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-76871.296, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71637.437, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-72450.553, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.703, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-77275.022, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76871.119, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71638.137, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72450.092, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-90455.404, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-77272.103, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-76872.774, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-71633.439, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-72455.690, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.111, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.260, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.111, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.279, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.260, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.111, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.278, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.260, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.111, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.278, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.261, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.103, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.273, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.132, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.257, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.146, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.848, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-88109.505, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-84036.770, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-82834.832, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-79472.793, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-59656.357, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-88109.526, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-84036.750, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-82834.852, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-79472.744, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-59656.349, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-88109.544, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-84036.584, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-82836.399, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-79473.466, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-59655.989, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88109.505, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-84036.772, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82834.828, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-79472.790, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59656.360, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-88109.851, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-84032.993, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-82835.529, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-79473.134, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-59653.940, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.111, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.279, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.261, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.111, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.280, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.260, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.111, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.281, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.261, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.142, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.111, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.279, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.261, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.097, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.270, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.131, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.144, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.740, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-78207.820, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-76871.868, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-71638.488, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-73110.755, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.746, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-78207.619, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-76871.886, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-71638.440, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-73110.866, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.717, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-78205.826, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-76871.979, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-71637.791, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-73112.004, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.739, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-78207.840, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76871.870, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71638.495, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-73110.743, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-90455.596, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-78187.272, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-76872.816, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-71633.768, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-73125.678, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 3.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 2.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 3.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.093, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.255, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.093, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.255, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.093, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.277, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.139, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.257, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.142, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.093, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.278, total= 4.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.255, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.093, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.275, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.137, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.851, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.903, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.851, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.903, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.851, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.903, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-88354.560, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-80592.205, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-81826.629, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-78882.007, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-59823.459, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-88354.629, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-80592.211, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-81826.666, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-78881.990, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-59823.439, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-88355.295, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-80592.298, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-81826.971, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-78882.207, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-59823.327, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88354.555, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-80592.205, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-81826.623, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-78882.009, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59823.460, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-88361.680, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-80595.317, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-81833.310, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-78882.261, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-59821.525, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 2.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 2.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 3.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.093, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.278, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.254, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.093, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.278, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.254, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.093, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.279, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.140, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.255, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.141, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.093, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.278, total= 6.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.254, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 2.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.090, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.278, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.145, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.851, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.903, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.851, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.903, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.852, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.884, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.851, total= 0.9s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.903, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.545, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-58825.988, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-76867.779, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-71636.542, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-72488.513, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.541, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-58825.999, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-76867.772, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-71636.483, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-72488.447, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.584, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-58826.293, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-76867.769, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-71636.001, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-72488.199, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.544, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-58825.984, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76867.779, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71636.548, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72488.517, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-90457.607, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-58828.019, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-76868.473, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-71631.412, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-72482.928, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 2.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 4.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.090, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.283, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.135, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.252, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.090, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.283, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.135, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.253, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.151, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.089, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.134, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.252, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.152, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.089, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.283, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.135, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.252, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.090, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.285, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.127, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.252, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.157, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-88352.575, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-56316.694, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-81824.023, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-78251.436, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-59432.351, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-88352.649, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-56316.697, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-81824.083, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-78251.549, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-59432.355, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-88353.442, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-56316.711, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-81824.395, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-78252.254, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-59432.551, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88352.569, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-56316.693, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-81824.018, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-78251.428, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59432.349, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-88358.358, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-56316.626, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-81827.992, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-78256.372, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-59433.516, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 2.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.9s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 2.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 2.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 8.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 6.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.089, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.283, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.135, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.253, total= 1.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.090, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.283, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.135, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.089, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.281, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.135, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.251, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.151, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.089, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.283, total= 1.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.135, total= 1.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.252, total= 1.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.7s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.093, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.283, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.135, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.249, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.149, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.5s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.884, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.884, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.8s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.884, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.6s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-89984.039, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-60893.921, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-76863.608, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71634.556, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-72492.705, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-89984.056, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-60893.905, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-76863.605, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71634.498, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-72492.671, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-89984.416, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-60893.887, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-76863.783, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71634.021, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-72492.448, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-89984.035, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-60893.922, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76863.607, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71634.562, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72492.708, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-89986.534, total= 0.1s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-60895.011, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-76862.126, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71629.474, total= 0.0s [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-72488.816, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 2.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 3.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.650, total= 3.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.702, total= 3.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.750, total= 5.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.650, total= 3.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.650, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.703, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.750, total= 2.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.650, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.649, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.703, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.651, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.650, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 6.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.702, total= 4.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.750, total= 13.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.650, total= 7.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.647, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.719, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.752, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.659, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.898, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.910, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.898, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.910, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.898, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.898, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.910, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.848, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-88748.180, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-82599.199, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-82834.901, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-79474.812, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-59656.559, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-88748.243, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-82599.303, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-82834.920, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-79474.841, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-59656.540, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-88748.614, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-82599.950, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-82836.739, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-79475.220, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-59656.381, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88748.176, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82599.190, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82834.894, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-79474.810, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59656.561, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-88751.726, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-82607.590, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-82836.446, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-79475.239, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-59654.376, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 4.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 3.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.702, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.750, total= 3.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.650, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.702, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.750, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.649, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.649, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.703, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.751, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.652, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 5.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 6.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.702, total= 2.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.750, total= 6.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 4.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.648, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.720, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.706, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.754, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.657, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.898, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.899, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.899, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.898, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.900, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.702, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-77275.021, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-76871.116, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71638.131, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-72450.092, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.696, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-77275.013, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-76871.142, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71638.083, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-72450.116, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.610, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-77274.941, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-76871.296, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71637.437, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-72450.553, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.703, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-77275.022, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76871.119, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71638.137, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72450.092, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-90455.404, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-77272.103, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-76872.774, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-71633.439, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-72455.690, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.651, total= 4.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.716, total= 4.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.705, total= 2.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.751, total= 3.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.649, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.651, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.716, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.705, total= 2.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.751, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.648, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.652, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.704, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.649, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.651, total= 6.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.716, total= 6.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.705, total= 3.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.751, total= 4.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.649, total= 4.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.651, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.717, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.707, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.752, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.649, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.849, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.897, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.882, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.897, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.882, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.848, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.897, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.882, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.910, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.849, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.897, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.882, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.898, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-88109.505, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-84036.770, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-82834.832, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-79472.793, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-59656.357, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-88109.526, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-84036.750, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-82834.852, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-79472.744, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-59656.349, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-88109.544, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-84036.584, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-82836.399, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-79473.466, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-59655.989, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88109.505, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-84036.772, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-82834.828, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-79472.790, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59656.360, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-88109.851, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-84032.993, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-82835.529, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-79473.134, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-59653.940, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.651, total= 6.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.716, total= 3.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.705, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.751, total= 6.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.648, total= 2.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.652, total= 2.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.716, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.704, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.751, total= 2.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.648, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.649, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.716, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.704, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.750, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.648, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.651, total= 9.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.716, total= 6.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.705, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.751, total= 6.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.649, total= 4.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.652, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.721, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.709, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.749, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.654, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.849, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.897, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.882, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.910, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.849, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.897, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.882, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.910, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.849, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.897, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.882, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.910, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.869, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.849, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.897, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.882, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.910, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.847, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.899, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.910, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.740, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-78207.820, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-76871.868, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-71638.488, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-73110.755, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.746, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-78207.619, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-76871.886, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-71638.440, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-73110.866, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.717, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-78205.826, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-76871.979, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-71637.791, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-73112.004, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.739, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-78207.840, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76871.870, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71638.495, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-73110.743, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-90455.596, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-78187.272, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-76872.816, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-71633.768, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-73125.678, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 3.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.755, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 3.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 2.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 5.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.728, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.653, total= 11.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 6.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.708, total= 8.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.762, total= 4.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.658, total= 3.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.653, total= 2.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.717, total= 4.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.708, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.762, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.658, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.652, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.707, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.762, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.661, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.653, total= 9.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 10.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.708, total= 9.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.762, total= 7.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.658, total= 4.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.642, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.762, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.675, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.851, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.903, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.872, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.851, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.903, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.872, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.883, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.851, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.903, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.872, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-88354.560, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-80592.205, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-81826.629, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-78882.007, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-59823.459, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-88354.629, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-80592.211, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-81826.666, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-78881.990, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-59823.439, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-88355.295, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-80592.298, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-81826.971, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-78882.207, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-59823.327, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88354.555, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-80592.205, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-81826.623, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-78882.009, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59823.460, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-88361.680, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-80595.317, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-81833.310, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-78882.261, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-59821.525, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 2.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.755, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 4.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.728, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.653, total= 3.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 7.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.708, total= 7.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.762, total= 5.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.658, total= 2.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.653, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.717, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.707, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.762, total= 2.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.658, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.651, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.716, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.706, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.763, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.662, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.653, total= 7.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 10.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.708, total= 9.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.762, total= 5.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.658, total= 4.3s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.644, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.710, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.765, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.676, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.851, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.903, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.883, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.872, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.851, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.903, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.883, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.872, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.852, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.851, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.903, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.883, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.872, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.903, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.911, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-90455.545, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-58825.988, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-76867.779, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-71636.542, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-72488.513, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-90455.541, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-58825.999, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-76867.772, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-71636.483, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-72488.447, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-90455.584, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-58826.293, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-76867.769, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-71636.001, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-72488.199, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90455.544, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-58825.984, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76867.779, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71636.548, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72488.517, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-90457.607, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-58828.019, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-76868.473, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-71631.412, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-72482.928, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 2.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 4.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.734, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.643, total= 3.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 2.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 5.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.761, total= 5.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.668, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.643, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.760, total= 1.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.668, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.647, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.712, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.760, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.667, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.643, total= 13.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 4.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 7.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.761, total= 8.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.668, total= 3.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.642, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.711, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.762, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.855, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.909, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.883, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.911, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.855, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.883, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.909, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.872, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.855, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.909, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.883, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.911, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.857, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.882, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-88352.575, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-56316.694, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-81824.023, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-78251.436, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-59432.351, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-88352.649, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-56316.697, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-81824.083, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-78251.549, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-59432.355, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-88353.442, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-56316.711, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-81824.395, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-78252.254, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-59432.551, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-88352.569, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-56316.693, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-81824.018, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-78251.428, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-59432.349, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-88358.358, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-56316.626, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-81827.992, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-78256.372, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-59433.516, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 1.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 4.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.773, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.734, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.643, total= 2.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 1.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.714, total= 3.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.761, total= 3.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.668, total= 2.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.643, total= 1.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.713, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.760, total= 2.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.667, total= 1.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.646, total= 1.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.760, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.669, total= 0.8s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.643, total= 7.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 3.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.714, total= 5.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.761, total= 7.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.668, total= 4.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.639, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.711, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.713, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.762, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.674, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.855, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.909, total= 0.5s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.884, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.911, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.855, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.909, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.884, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.911, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.855, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.909, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.884, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.911, total= 0.2s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.872, total= 0.3s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.855, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.909, total= 0.9s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.884, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.911, total= 0.7s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.6s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.855, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.909, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.883, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.872, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-89984.039, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-60893.921, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-76863.608, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-71634.556, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-72492.705, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-89984.056, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-60893.905, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-76863.605, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-71634.498, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-72492.671, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-89984.416, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-60893.887, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-76863.783, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-71634.021, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-72492.448, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-89984.035, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-60893.922, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-76863.607, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-71634.562, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-72492.708, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-89986.534, total= 0.1s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-60895.011, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-76862.126, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-71629.474, total= 0.0s [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=800, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-72488.816, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 3.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 3.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 4.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=-0.103, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.280, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.257, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.146, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=-0.103, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.280, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.145, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.257, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.146, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=-0.103, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.279, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.258, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.147, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=-0.103, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.280, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.257, total= 1.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.146, total= 4.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=-0.096, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.278, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.130, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.252, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.845, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.913, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.845, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.913, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.846, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-137902.987, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-93779.134, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122810.646, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122283.490, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-91431.998, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-137902.965, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-93779.148, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122810.641, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122283.374, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-91431.983, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-137902.837, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-93779.290, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122810.686, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122282.916, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-91432.045, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-137902.988, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-93779.133, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122810.646, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122283.506, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91431.998, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-137901.111, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-93781.720, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-122812.809, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-122271.213, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-91433.359, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 4.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=-0.103, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.280, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.257, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.146, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=-0.103, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.280, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.145, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.257, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.146, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=-0.103, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.278, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.257, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.147, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=-0.103, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.280, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.257, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.146, total= 2.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=-0.106, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.280, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.129, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.255, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.142, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 1.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.844, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.892, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.244, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-91016.682, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-125817.916, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-99996.739, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-92861.598, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-91016.713, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-125817.950, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-99996.890, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-92861.618, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-91017.009, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.354, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-99998.729, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-92861.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.243, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-91016.679, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125817.909, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-99996.727, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92861.593, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-123186.870, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-91018.776, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-125822.098, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-100013.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-92864.722, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 2.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=-0.111, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.274, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.260, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=-0.112, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.274, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.261, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=-0.111, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.272, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.144, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.261, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=-0.111, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.274, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.260, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=-0.105, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.270, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.129, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.256, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.144, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.875, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.842, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.890, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-123015.467, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-93779.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-122811.825, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-122281.873, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-91431.609, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-123015.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-93779.445, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-122811.835, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-122281.776, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-91431.608, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-123015.527, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-93779.284, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-122811.848, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-122281.506, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-91431.692, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-123015.467, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-93779.461, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122811.824, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122281.892, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91431.610, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-123015.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-93777.076, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-122814.783, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-122269.665, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-91435.039, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 3.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=-0.111, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.274, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.260, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=-0.111, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.274, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.260, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=-0.113, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.274, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.144, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.260, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=-0.111, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.274, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.260, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=-0.109, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.275, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.131, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.258, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.146, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.889, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.889, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.889, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.875, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.575, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-91016.997, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-125818.023, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-99994.085, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-92861.345, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.593, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-91017.020, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-125818.059, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-99994.237, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-92861.373, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.739, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-91017.291, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.450, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-99996.103, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-92861.627, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.572, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-91016.995, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125818.018, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-99994.073, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92861.343, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-123187.710, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-91019.494, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-125822.018, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-100011.031, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-92863.673, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 2.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 2.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 2.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 3.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=-0.095, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.278, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.142, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.254, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.144, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=-0.094, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.278, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.142, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.254, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.144, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=-0.093, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.278, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.141, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.255, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.142, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=-0.095, total= 3.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.278, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.142, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.254, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.144, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=-0.090, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.280, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.136, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.254, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.149, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.850, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.893, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.850, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.893, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.913, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.850, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.893, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.850, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.893, total= 1.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.913, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.851, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.878, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-137902.898, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-89673.983, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-122806.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-124869.265, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-91433.726, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-137902.881, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-89673.999, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-122806.445, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-124869.264, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-91433.741, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-137902.416, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-89673.968, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-122806.057, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-124869.204, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-91433.855, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-137902.902, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-89673.981, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122806.469, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-124869.265, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91433.726, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-137899.454, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-89675.206, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-122806.127, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-124867.926, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-91434.218, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 2.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 2.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 3.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 4.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 3.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=-0.095, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.278, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.142, total= 1.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.254, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.144, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=-0.094, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.278, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.142, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.254, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.144, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=-0.092, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.278, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.140, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.256, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.143, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=-0.095, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.278, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.142, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.254, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.144, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=-0.095, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.282, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.138, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.260, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.146, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.850, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.894, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.850, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.894, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.850, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.894, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.850, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.894, total= 1.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 1.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.851, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.879, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.526, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-90076.827, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-125817.428, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-100332.639, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-98898.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.527, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-90076.817, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-125817.532, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-100332.647, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-98898.225, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.672, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-90076.800, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.300, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-100332.624, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-98897.744, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.526, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90076.828, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125817.424, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-100332.637, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-98898.277, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-123187.614, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-90078.875, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-125819.669, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-100336.434, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-98892.008, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 2.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 2.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 2.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 2.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 3.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=-0.089, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.284, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.136, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.253, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.152, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=-0.090, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.284, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.136, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.253, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.152, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=-0.088, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.284, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.134, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.253, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.152, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=-0.089, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.284, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.136, total= 1.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.253, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.152, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=-0.086, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.288, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.136, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.255, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.151, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.874, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-141500.113, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-96405.474, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122801.309, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-124870.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-91435.891, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-141500.115, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-96405.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122801.281, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-124870.959, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-91435.870, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-141500.294, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-96405.481, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122801.086, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-124870.985, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-91435.389, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-141500.109, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-96405.475, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122801.313, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-124870.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91435.892, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-141499.914, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-96405.221, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-122799.002, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-124869.767, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-91432.920, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 2.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 2.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 1.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 2.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 3.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 1.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=-0.089, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.284, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.136, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.253, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.152, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=-0.090, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.284, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.136, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.252, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.152, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=-0.090, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.283, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.135, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.254, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.151, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=-0.089, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.284, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.136, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.253, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.152, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=-0.088, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.288, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.134, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.253, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.152, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 0.9s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.8s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.7s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.877, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.874, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-123184.276, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-95195.352, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-124848.247, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-100331.102, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-92509.090, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-123184.288, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-95195.363, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-124848.344, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-100331.104, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-92509.103, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-123184.387, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-95195.441, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-124849.129, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-100331.285, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-92509.141, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123184.274, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-95195.351, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-124848.238, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-100331.097, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92509.088, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-123185.604, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-95196.508, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-124856.246, total= 0.0s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-100332.984, total= 0.1s [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=2, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-92509.512, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.01, score=0.728, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.773, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 4.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.647, total= 5.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 4.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.704, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.751, total= 4.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.001, score=0.647, total= 4.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.647, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.714, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.704, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.750, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.01, score=0.646, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.647, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.714, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.705, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.1, score=0.648, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.647, total= 6.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 14.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.704, total= 4.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.751, total= 9.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=0.0001, score=0.647, total= 7.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.646, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.705, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.755, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=poly, tol=1, score=0.651, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.845, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.890, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.913, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.890, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.913, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.890, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.845, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.890, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.913, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.846, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.891, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=rbf, tol=1, score=0.871, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-137902.987, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-93779.134, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122810.646, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122283.490, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.001, score=-91431.998, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-137902.965, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-93779.148, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122810.641, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122283.374, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.01, score=-91431.983, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-137902.837, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-93779.290, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122810.686, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122282.916, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.1, score=-91432.045, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-137902.988, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-93779.133, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122810.646, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122283.506, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91431.998, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-137901.111, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-93781.720, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-122812.809, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-122271.213, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=scale, kernel=sigmoid, tol=1, score=-91433.359, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 4.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.01, score=0.728, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 3.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 4.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.809, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.647, total= 4.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 5.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.704, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.751, total= 8.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.001, score=0.647, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.647, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.704, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.751, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.01, score=0.646, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.646, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.714, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.703, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.751, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.1, score=0.645, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.647, total= 6.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 6.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.704, total= 7.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.751, total= 14.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=0.0001, score=0.647, total= 5.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.644, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.716, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.705, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.755, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=poly, tol=1, score=0.653, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.890, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.890, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.890, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.890, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.844, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.892, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.878, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=rbf, tol=1, score=0.870, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.244, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-91016.682, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-125817.916, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-99996.739, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.001, score=-92861.598, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-91016.713, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-125817.950, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-99996.890, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.01, score=-92861.618, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-91017.009, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.354, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-99998.729, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.1, score=-92861.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.243, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-91016.679, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125817.909, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-99996.727, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92861.593, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-123186.870, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-91018.776, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-125822.098, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-100013.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.1, gamma=auto, kernel=sigmoid, tol=1, score=-92864.722, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.757, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.1, score=0.728, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.808, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.649, total= 9.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.715, total= 3.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.705, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.751, total= 5.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.001, score=0.650, total= 7.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.648, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.715, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.705, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.751, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.01, score=0.649, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.650, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.716, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.701, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.751, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.1, score=0.648, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.649, total= 27.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.715, total= 4.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.705, total= 3.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.751, total= 5.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=0.0001, score=0.650, total= 10.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.652, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.718, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.703, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.750, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=poly, tol=1, score=0.650, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.846, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.888, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.001, score=0.870, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.845, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.888, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.01, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.888, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.875, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.1, score=0.870, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.846, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.888, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=0.0001, score=0.870, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.842, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.890, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-123015.467, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-93779.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-122811.825, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-122281.873, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.001, score=-91431.609, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-123015.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-93779.445, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-122811.835, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-122281.776, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.01, score=-91431.608, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-123015.527, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-93779.284, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-122811.848, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-122281.506, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.1, score=-91431.692, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-123015.467, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-93779.461, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122811.824, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122281.892, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91431.610, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-123015.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-93777.076, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-122814.783, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-122269.665, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=scale, kernel=sigmoid, tol=1, score=-91435.039, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.757, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.1, score=0.728, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.756, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.755, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.808, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=linear, tol=1, score=0.727, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.649, total= 10.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.715, total= 5.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.705, total= 3.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.751, total= 4.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 4.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.649, total= 4.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.715, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.705, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.751, total= 3.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.01, score=0.649, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.651, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.705, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.751, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.1, score=0.646, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.649, total= 14.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.715, total= 13.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.705, total= 3.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.751, total= 6.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 9.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.650, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.717, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.705, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.749, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=poly, tol=1, score=0.649, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.845, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.889, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.912, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.001, score=0.870, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.845, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.889, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.912, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.01, score=0.870, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.845, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.889, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.912, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.1, score=0.870, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.845, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.889, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.912, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=0.0001, score=0.870, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.842, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.889, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.875, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=rbf, tol=1, score=0.869, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.575, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-91016.997, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-125818.023, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-99994.085, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.001, score=-92861.345, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.593, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-91017.020, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-125818.059, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-99994.237, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.01, score=-92861.373, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.739, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-91017.291, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.450, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-99996.103, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.1, score=-92861.627, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.572, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-91016.995, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125818.018, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-99994.073, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92861.343, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-123187.710, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-91019.494, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-125822.018, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-100011.031, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.01, gamma=auto, kernel=sigmoid, tol=1, score=-92863.673, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.755, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.757, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.809, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.001, score=0.727, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.773, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.757, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.809, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.01, score=0.727, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.772, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.809, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.1, score=0.727, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.755, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.773, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.757, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.809, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=0.0001, score=0.727, total= 3.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.755, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.772, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.809, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=linear, tol=1, score=0.729, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.651, total= 5.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.718, total= 10.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.711, total= 4.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.761, total= 3.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.001, score=0.654, total= 3.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.650, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.718, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.710, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.761, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.01, score=0.654, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.649, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.717, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.710, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.761, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.1, score=0.659, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.650, total= 7.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.718, total= 15.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.711, total= 6.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.761, total= 7.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=0.0001, score=0.654, total= 5.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.645, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.712, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.711, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.761, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=poly, tol=1, score=0.677, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.850, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.893, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.878, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.913, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.850, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.893, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.878, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.913, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.850, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.893, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.878, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.850, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.893, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.878, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.913, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.851, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.894, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.878, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=rbf, tol=1, score=0.872, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-137902.898, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-89673.983, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-122806.468, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-124869.265, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.001, score=-91433.726, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-137902.881, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-89673.999, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-122806.445, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-124869.264, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.01, score=-91433.741, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-137902.416, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-89673.968, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-122806.057, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-124869.204, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.1, score=-91433.855, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-137902.902, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-89673.981, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122806.469, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-124869.265, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91433.726, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-137899.454, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-89675.206, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-122806.127, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-124867.926, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=scale, kernel=sigmoid, tol=1, score=-91434.218, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.755, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.773, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.757, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.809, total= 3.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.001, score=0.727, total= 3.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.773, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.757, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.809, total= 3.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.01, score=0.727, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.772, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.809, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.1, score=0.727, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.755, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.773, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.757, total= 4.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.809, total= 3.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=0.0001, score=0.727, total= 5.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.755, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.772, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.757, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.809, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=linear, tol=1, score=0.729, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.650, total= 7.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.718, total= 7.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.711, total= 6.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.761, total= 5.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.001, score=0.654, total= 3.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.650, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.718, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.710, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.761, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.01, score=0.654, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.648, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.717, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.710, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.761, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.1, score=0.656, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.650, total= 7.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.718, total= 9.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.711, total= 7.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.761, total= 9.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=0.0001, score=0.654, total= 3.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.643, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.718, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.760, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=poly, tol=1, score=0.672, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.850, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.894, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.878, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.850, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.894, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.878, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.850, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.894, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.878, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.850, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.894, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.878, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 1.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.851, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.894, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.879, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=rbf, tol=1, score=0.871, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-123185.526, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-90076.827, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-125817.428, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-100332.639, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.001, score=-98898.273, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-123185.527, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-90076.817, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-125817.532, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-100332.647, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.01, score=-98898.225, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-123185.672, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-90076.800, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-125818.300, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-100332.624, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.1, score=-98897.744, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123185.526, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-90076.828, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-125817.424, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-100332.637, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=0.0001, score=-98898.277, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-123187.614, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-90078.875, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-125819.669, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-100336.434, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=0.5, gamma=auto, kernel=sigmoid, tol=1, score=-98892.008, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.756, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.774, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.758, total= 2.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.810, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.001, score=0.731, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.756, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.774, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.758, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.810, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.01, score=0.731, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.756, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.758, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.810, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.1, score=0.731, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.756, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.774, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.758, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.810, total= 3.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=0.0001, score=0.731, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.774, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.758, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.810, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=linear, tol=1, score=0.733, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.638, total= 5.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.714, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.713, total= 4.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.760, total= 5.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.001, score=0.668, total= 2.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.639, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.713, total= 2.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.760, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.01, score=0.669, total= 1.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.638, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.712, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.713, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.760, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.1, score=0.666, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.638, total= 6.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.714, total= 6.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.713, total= 6.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.760, total= 15.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=0.0001, score=0.668, total= 8.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.637, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.709, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.714, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.758, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=poly, tol=1, score=0.672, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.854, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.900, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.912, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.001, score=0.873, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.854, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.900, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.876, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.912, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.01, score=0.873, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.853, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.901, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.876, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.912, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.854, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.900, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.876, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.912, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=0.0001, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.852, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.899, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.877, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=rbf, tol=1, score=0.874, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-141500.113, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-96405.474, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-122801.309, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-124870.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.001, score=-91435.891, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-141500.115, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-96405.459, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-122801.281, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-124870.959, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.01, score=-91435.870, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-141500.294, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-96405.481, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-122801.086, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-124870.985, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.1, score=-91435.389, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-141500.109, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-96405.475, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-122801.313, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-124870.964, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=0.0001, score=-91435.892, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-141499.914, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-96405.221, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-122799.002, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-124869.767, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=scale, kernel=sigmoid, tol=1, score=-91432.920, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.756, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.774, total= 2.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.758, total= 3.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.810, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.001, score=0.731, total= 2.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.756, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.774, total= 2.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.758, total= 2.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.810, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.01, score=0.731, total= 1.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.756, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.774, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.758, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.810, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.1, score=0.731, total= 1.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.756, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.774, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.758, total= 2.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.810, total= 3.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=0.0001, score=0.731, total= 1.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.757, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.774, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.758, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.810, total= 1.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=linear, tol=1, score=0.733, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.638, total= 4.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 2.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.713, total= 5.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.760, total= 6.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.001, score=0.668, total= 5.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.638, total= 2.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 1.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.714, total= 2.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.761, total= 2.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.01, score=0.668, total= 1.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.638, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.713, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.761, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.1, score=0.669, total= 0.9s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.638, total= 6.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 5.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.713, total= 4.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.760, total= 6.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=0.0001, score=0.668, total= 12.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.632, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.711, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.712, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.759, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=poly, tol=1, score=0.673, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.854, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.901, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.876, total= 0.6s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.913, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.001, score=0.873, total= 0.5s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.854, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.901, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.876, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.01, score=0.873, total= 0.4s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.853, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.901, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.876, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.913, total= 0.3s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.1, score=0.873, total= 0.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.854, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.901, total= 1.2s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.876, total= 1.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.913, total= 0.7s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=0.0001, score=0.873, total= 0.8s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.852, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.901, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.877, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.913, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=rbf, tol=1, score=0.874, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-123184.276, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-95195.352, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-124848.247, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-100331.102, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.001, score=-92509.090, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-123184.288, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-95195.363, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-124848.344, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-100331.104, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.01, score=-92509.103, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-123184.387, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-95195.441, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-124849.129, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-100331.285, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.1, score=-92509.141, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-123184.274, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-95195.351, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-124848.238, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-100331.097, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=0.0001, score=-92509.088, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-123185.604, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-95196.508, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-124856.246, total= 0.1s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-100332.984, total= 0.0s [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1 [CV] C=1000, coef0=0.0, degree=3, epsilon=1, gamma=auto, kernel=sigmoid, tol=1, score=-92509.512, total= 0.1s
[Parallel(n_jobs=1)]: Done 24000 out of 24000 | elapsed: 138.6min finished
Out[470]:
GridSearchCV(cv=None, error_score=nan,
estimator=SVR(C=1.0, cache_size=200, coef0=0.0, degree=3,
epsilon=0.1, gamma='scale', kernel='rbf',
max_iter=-1, shrinking=True, tol=0.001,
verbose=False),
iid='deprecated', n_jobs=None,
param_grid={'C': [0.1, 0.5, 1, 5, 10, 25, 50, 75, 100, 200, 350,
500, 750, 800, 1000],
'coef0': [0.0], 'degree': [2, 3],
'epsilon': [0.1, 0.01, 0.5, 1],
'gamma': ['scale', 'auto'],
'kernel': ['linear', 'poly', 'rbf', 'sigmoid'],
'tol': [0.001, 0.01, 0.1, 0.0001, 1]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [471]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'C': 350, 'coef0': 0.0, 'degree': 2, 'epsilon': 1, 'gamma': 'auto', 'kernel': 'rbf', 'tol': 1}
0.8935750951075683
SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False)
In [528]:
svr = SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False)
In [529]:
svr.fit(X_train_scaled,y_train)
print("The score on train data: ",svr.score(X_train_scaled,y_train))
print("\nThe score on test data: ",svr.score(X_test_scaled,y_test))
The score on train data: 0.9621382098442767 The score on test data: 0.8822086282534799
In [530]:
y_pred = svr.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# Clearly svr has a good score and good r-square value and RMSE
The RMSE score is 5.725794336377752 The R-squared value is 0.8746572275634272
In [531]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [532]:
model= "Support Vector Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
84.35% to 95.53% 3.59 to 6.65 0.83 to 0.95
In [492]:
e = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'84.35% to 95.53%',
'RMSE':'3.59 to 6.65','R-squared':'0.83 to 0.95'} ,index=[5])
e
Out[492]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 5 | Support Vector Regressor | 84.35% to 95.53% | 3.59 to 6.65 | 0.83 to 0.95 |
KNN Regressor¶
In [511]:
param_grid = {
'n_neighbors':[1,2,3,4,5],
'weights':['uniform','distance'],
'algorithm':['auto'],
'p':[1,2],
'metric':['minkowski'],
}
In [512]:
grid = GridSearchCV(KNeighborsRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 20 candidates, totalling 100 fits [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform, score=0.589, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform, score=0.720, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform, score=0.751, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform, score=0.707, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=uniform, score=0.714, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance, score=0.589, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance, score=0.720, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance, score=0.751, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance, score=0.707, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=1, weights=distance, score=0.714, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform, score=0.639, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform, score=0.765, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform, score=0.804, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform, score=0.760, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=uniform, score=0.759, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance, score=0.639, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance, score=0.765, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance, score=0.804, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance, score=0.760, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=1, p=2, weights=distance, score=0.759, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform, score=0.632, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform, score=0.726, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform, score=0.765, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform, score=0.772, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=uniform, score=0.694, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance, score=0.669, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance, score=0.762, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance, score=0.790, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance, score=0.773, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=1, weights=distance, score=0.754, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform, score=0.710, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform, score=0.795, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform, score=0.819, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform, score=0.823, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers. [Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=uniform, score=0.743, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance, score=0.721, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance, score=0.816, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance, score=0.838, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance, score=0.825, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=2, p=2, weights=distance, score=0.780, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform, score=0.687, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform, score=0.788, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform, score=0.777, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform, score=0.789, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=uniform, score=0.682, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance, score=0.731, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance, score=0.806, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance, score=0.813, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance, score=0.799, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=1, weights=distance, score=0.769, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform, score=0.759, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform, score=0.800, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform, score=0.813, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform, score=0.822, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=uniform, score=0.743, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance, score=0.766, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance, score=0.827, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance, score=0.841, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance, score=0.831, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=3, p=2, weights=distance, score=0.796, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform, score=0.724, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform, score=0.806, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform, score=0.763, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform, score=0.799, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=uniform, score=0.704, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance, score=0.756, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance, score=0.830, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance, score=0.804, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance, score=0.810, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=1, weights=distance, score=0.782, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform, score=0.755, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform, score=0.799, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform, score=0.819, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform, score=0.817, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=uniform, score=0.729, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance, score=0.770, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance, score=0.837, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance, score=0.844, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance, score=0.836, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=4, p=2, weights=distance, score=0.793, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform, score=0.748, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform, score=0.809, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform, score=0.751, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform, score=0.793, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=uniform, score=0.720, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance, score=0.771, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance, score=0.841, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance, score=0.806, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance, score=0.814, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=1, weights=distance, score=0.794, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform, score=0.778, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform, score=0.810, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform, score=0.809, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform, score=0.800, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=uniform, score=0.731, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance, score=0.797, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance, score=0.851, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance, score=0.840, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance, score=0.828, total= 0.0s [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance [CV] algorithm=auto, metric=minkowski, n_neighbors=5, p=2, weights=distance, score=0.803, total= 0.0s
[Parallel(n_jobs=1)]: Done 100 out of 100 | elapsed: 0.7s finished
Out[512]:
GridSearchCV(cv=None, error_score=nan,
estimator=KNeighborsRegressor(algorithm='auto', leaf_size=30,
metric='minkowski',
metric_params=None, n_jobs=None,
n_neighbors=5, p=2,
weights='uniform'),
iid='deprecated', n_jobs=None,
param_grid={'algorithm': ['auto'], 'metric': ['minkowski'],
'n_neighbors': [1, 2, 3, 4, 5], 'p': [1, 2],
'weights': ['uniform', 'distance']},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [513]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'algorithm': 'auto', 'metric': 'minkowski', 'n_neighbors': 5, 'p': 2, 'weights': 'distance'}
0.823851373940421
KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',
metric_params=None, n_jobs=None, n_neighbors=5, p=2,
weights='distance')
In [514]:
knn = KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',
metric_params=None, n_jobs=None, n_neighbors=5, p=2,
weights='distance')
In [515]:
knn.fit(X_train_scaled,y_train)
print("The score on train data: ",knn.score(X_train_scaled,y_train))
print("\nThe score on test data: ",knn.score(X_test_scaled,y_test))
The score on train data: 0.995594292367634 The score on test data: 0.8214490370409486
In [517]:
y_pred = knn.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# KNN regressor has good score on train set, and average scores on test set. But there are better models than KNN regressor
The RMSE score is 7.049529030091715 The R-squared value is 0.745040663099283
In [520]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',
metric_params=None, n_jobs=None, n_neighbors=5, p=2,
weights='distance')
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [521]:
model= "KNN Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
80.66% to 89.07% 4.91 to 7.76 0.73 to 0.88
In [523]:
f = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'80.66% to 89.07%',
'RMSE':'4.91 to 7.76','R-squared':'0.73 to 0.88'} ,index=[6])
f
Out[523]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 6 | KNN Regressor | 80.66% to 89.07% | 4.91 to 7.76 | 0.73 to 0.88 |
ADABOOST REGRESSOR¶
In [534]:
param_grid = {
'base_estimator':[svr],
'n_estimators':[50,100,150],
'learning_rate':[1.0,0.5],
'loss':['linear','square'],
'random_state':[seed],
}
In [535]:
grid = GridSearchCV(AdaBoostRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 12 candidates, totalling 60 fits
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10, score=0.858, total= 2.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10
[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 2.6s remaining: 0.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10, score=0.892, total= 3.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10
[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 5.8s remaining: 0.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10, score=0.901, total= 4.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10, score=0.917, total= 3.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=50, random_state=10, score=0.868, total= 2.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10, score=0.839, total= 4.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10, score=0.849, total= 4.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10, score=0.893, total= 5.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10, score=0.887, total= 4.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=100, random_state=10, score=0.841, total= 4.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10, score=0.819, total= 6.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10, score=0.826, total= 5.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10, score=0.889, total= 7.9s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10, score=0.852, total= 7.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=linear, n_estimators=150, random_state=10, score=0.830, total= 6.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10, score=0.858, total= 1.5s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10, score=0.852, total= 2.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10, score=0.881, total= 2.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10, score=0.880, total= 2.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=50, random_state=10, score=0.835, total= 2.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10, score=0.858, total= 1.4s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10, score=0.783, total= 3.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10, score=0.867, total= 4.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10, score=0.827, total= 4.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=100, random_state=10, score=0.799, total= 4.8s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10, score=0.858, total= 1.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10, score=0.741, total= 7.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10, score=0.855, total= 6.8s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10, score=0.794, total= 6.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=1.0, loss=square, n_estimators=150, random_state=10, score=0.755, total= 6.4s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10, score=0.863, total= 2.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10, score=0.918, total= 3.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10, score=0.899, total= 3.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10, score=0.925, total= 3.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=50, random_state=10, score=0.876, total= 3.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10, score=0.863, total= 2.9s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10, score=0.918, total= 3.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10, score=0.895, total= 6.4s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10, score=0.917, total= 5.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=100, random_state=10, score=0.876, total= 2.5s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10, score=0.863, total= 2.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10, score=0.918, total= 3.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10, score=0.891, total= 9.8s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10, score=0.907, total= 7.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=linear, n_estimators=150, random_state=10, score=0.876, total= 2.5s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10, score=0.870, total= 2.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10, score=0.902, total= 2.4s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10, score=0.899, total= 3.0s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10, score=0.915, total= 2.6s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=50, random_state=10, score=0.865, total= 3.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10, score=0.835, total= 6.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10, score=0.860, total= 5.3s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10, score=0.887, total= 5.8s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10, score=0.894, total= 8.7s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=100, random_state=10, score=0.850, total= 8.2s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10, score=0.810, total= 10.4s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10, score=0.819, total= 12.8s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10, score=0.880, total= 11.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10, score=0.860, total= 8.1s
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10
[CV] base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), learning_rate=0.5, loss=square, n_estimators=150, random_state=10, score=0.826, total= 7.4s
[Parallel(n_jobs=1)]: Done 60 out of 60 | elapsed: 4.8min finished
Out[535]:
GridSearchCV(cv=None, error_score=nan,
estimator=AdaBoostRegressor(base_estimator=None, learning_rate=1.0,
loss='linear', n_estimators=50,
random_state=None),
iid='deprecated', n_jobs=None,
param_grid={'base_estimator': [SVR(C=350, cache_size=200,
coef0=0.0, degree=2, epsilon=1,
gamma='auto', kernel='rbf',
max_iter=-1, shrinking=True,
tol=1, verbose=False)],
'learning_rate': [1.0, 0.5],
'loss': ['linear', 'square'],
'n_estimators': [50, 100, 150], 'random_state': [10]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [536]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'base_estimator': SVR(C=350, cache_size=200, coef0=0.0, degree=2, epsilon=1, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=1, verbose=False), 'learning_rate': 0.5, 'loss': 'linear', 'n_estimators': 50, 'random_state': 10}
0.8960544886114838
AdaBoostRegressor(base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2,
epsilon=1, gamma='auto', kernel='rbf',
max_iter=-1, shrinking=True, tol=1,
verbose=False),
learning_rate=0.5, loss='linear', n_estimators=50,
random_state=10)
In [550]:
adab = AdaBoostRegressor(base_estimator=svr,
learning_rate=0.5, loss='linear', n_estimators=50,
random_state=10)
In [551]:
adab.fit(X_train_scaled,y_train)
print("The score on train data: ",adab.score(X_train_scaled,y_train))
print("\nThe score on test data: ",adab.score(X_test_scaled,y_test))
The score on train data: 0.9678795786062587 The score on test data: 0.8884722475444354
In [552]:
y_pred = adab.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# Adaboost has a very good score of 88% and r2 of 87%
The RMSE score is 5.571478770740155 The R-squared value is 0.8736558428444001
In [540]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = AdaBoostRegressor(base_estimator=SVR(C=350, cache_size=200, coef0=0.0, degree=2,
epsilon=1, gamma='auto', kernel='rbf',
max_iter=-1, shrinking=True, tol=1,
verbose=False),
learning_rate=0.5, loss='linear', n_estimators=50,
random_state=10)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [541]:
model= "Ada Boost Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
86.40% to 95.06% 3.44 to 6.43 0.84 to 0.95
In [543]:
g = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'86.40% to 95.06%',
'RMSE':'3.44 to 6.43','R-squared':'0.84 to 0.95'} ,index=[7])
g
Out[543]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 7 | Ada Boost Regressor | 86.40% to 95.06% | 3.44 to 6.43 | 0.84 to 0.95 |
GRADIENT BOOSTING REGRESSOR¶
In [545]:
param_grid={
'loss':['ls','lad'],
'learning_rate':[0.1,0.5,1],
'n_estimators':[50,100,150],
'subsample':[1.0],
'criterion':['friedman_mse',"mse"],
'min_samples_split':[4],
'min_samples_leaf':[1],
'min_weight_fraction_leaf':[0.0],
'max_depth':[3,4,5,6],
'random_state':[seed],
}
In [547]:
grid = GridSearchCV(GradientBoostingRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 144 candidates, totalling 720 fits [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
[CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.845, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.861, total= 0.1s
[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.2s remaining: 0.0s
[CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.887, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.866, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.886, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.912, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.873, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.916, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.900, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.866, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.904, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.890, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.910, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.889, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.884, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.924, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.909, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.888, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.930, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.934, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.882, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.925, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.902, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.924, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.908, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.935, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.915, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.936, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.923, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.894, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.938, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.918, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.938, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.928, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.882, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.933, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.907, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.919, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.896, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.940, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.927, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.905, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.890, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.942, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.912, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.929, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.909, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.841, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.854, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.837, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.875, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.855, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.867, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.886, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.868, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.894, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.868, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.895, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.876, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.900, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.891, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.856, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.856, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.880, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.881, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.876, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.909, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.901, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.913, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.883, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.906, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.904, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.869, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.916, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.890, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.888, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.917, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.924, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.903, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.892, total= 1.0s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.919, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.883, total= 1.0s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.926, total= 1.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.908, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.873, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.909, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.870, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.898, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.897, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.883, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.893, total= 1.1s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.928, total= 1.4s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 1.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 1.7s [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.905, total= 1.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.917, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.889, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.923, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.910, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.872, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.896, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.933, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.918, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.871, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.932, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.897, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.939, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.915, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.934, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.882, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.923, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.899, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.935, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.913, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.899, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.936, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.913, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.928, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.920, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.935, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.909, total= 0.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.881, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.927, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.920, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.932, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.926, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.920, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.931, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.909, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.868, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.932, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.912, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.928, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.892, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.868, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.932, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.912, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.928, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.891, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.867, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.931, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.911, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.927, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.891, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.865, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.902, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.877, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.897, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.869, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.906, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.902, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.876, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.901, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.902, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.905, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.858, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.898, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.876, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.880, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.2s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.858, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.883, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.884, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.892, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.870, total= 0.6s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.905, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.885, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.896, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.846, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.3s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.848, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.916, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.882, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.898, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.901, total= 0.7s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.846, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.889, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.901, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.903, total= 1.0s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.859, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.917, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.862, total= 1.0s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.912, total= 0.9s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.876, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.918, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.894, total= 0.8s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.862, total= 1.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.918, total= 1.4s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.878, total= 1.1s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.918, total= 1.5s [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.895, total= 1.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.835, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.834, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.843, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.834, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.887, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.922, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.864, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.852, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.838, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.859, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.800, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.820, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.883, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.901, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.859, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.797, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.827, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.887, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.906, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.861, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.797, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.828, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.887, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.904, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.860, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.774, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.866, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.883, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.819, total= 0.1s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.779, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.862, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.885, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.820, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.779, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.862, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.885, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.878, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.819, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.810, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.870, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.878, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.798, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.809, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.868, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.798, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.809, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.879, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.868, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.879, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.798, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.842, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.848, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.843, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.851, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.858, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.833, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.862, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.842, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.856, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.864, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.840, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.862, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.842, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.856, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.864, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.757, total= 0.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.848, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.838, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.826, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.811, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.760, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.848, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.837, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.834, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.815, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.760, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.848, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.837, total= 0.5s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.833, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.815, total= 0.8s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.748, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.845, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.829, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.818, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.839, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.749, total= 0.6s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.848, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.836, total= 0.6s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.818, total= 0.6s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.840, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.747, total= 1.0s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.849, total= 1.0s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.836, total= 0.8s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.818, total= 0.8s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.836, total= 0.9s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.694, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.807, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.784, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.852, total= 0.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.814, total= 0.4s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.680, total= 0.9s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.807, total= 0.6s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.784, total= 0.9s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.859, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.812, total= 0.7s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.682, total= 1.3s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.810, total= 1.2s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.784, total= 1.1s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.859, total= 1.0s [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=friedman_mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.814, total= 1.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.845, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.861, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.887, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.866, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.886, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.912, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.873, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.916, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.900, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.866, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.904, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.890, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.910, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.889, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.884, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.924, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.909, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.888, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.930, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.934, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.882, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.925, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.902, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.924, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.908, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.935, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.915, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.936, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.923, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.894, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.938, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.918, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.938, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.928, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.932, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.906, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.920, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.896, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.939, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.927, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.906, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.890, total= 0.5s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.941, total= 0.5s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.912, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.929, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.909, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.841, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.854, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.837, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.875, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.855, total= 0.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.867, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.886, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.868, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.894, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.868, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.895, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.876, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.900, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.891, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.856, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.856, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.880, total= 0.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.881, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.876, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.909, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.901, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.913, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.883, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.906, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.904, total= 0.5s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.869, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.916, total= 0.3s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.890, total= 0.5s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.888, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.917, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 1.0s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.922, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.903, total= 0.6s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.892, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.919, total= 1.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.883, total= 1.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.927, total= 1.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.908, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.873, total= 0.6s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.909, total= 0.6s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.870, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.898, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.898, total= 0.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.890, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.883, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.911, total= 0.7s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.910, total= 0.8s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.893, total= 1.4s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.928, total= 1.2s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 1.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.914, total= 1.1s [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.912, total= 1.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.917, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.889, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.923, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.910, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.872, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.926, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.896, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.933, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.918, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.871, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.932, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.897, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.939, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.915, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.934, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.882, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.923, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.899, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.935, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.913, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.899, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.936, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.913, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.928, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.920, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.935, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.909, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.881, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.927, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.920, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.932, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.908, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.926, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.920, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.931, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.909, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.867, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.932, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.912, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.928, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.892, total= 0.1s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.867, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.932, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.912, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.928, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.891, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.866, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.931, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.911, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.927, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.891, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.865, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.902, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.877, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.897, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.869, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.906, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.880, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.902, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.876, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.901, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.882, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.902, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.905, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.858, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.898, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.876, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.880, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.858, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.904, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.883, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.884, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.892, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.870, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.905, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.885, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.896, total= 0.7s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.846, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.895, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.848, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.916, total= 0.5s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.882, total= 0.4s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.898, total= 0.7s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.901, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.846, total= 0.8s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.921, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.889, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.901, total= 0.7s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.903, total= 0.7s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.857, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.910, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.917, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.894, total= 0.3s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.861, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.917, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.876, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.918, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.894, total= 0.6s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.860, total= 0.9s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.920, total= 0.8s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.878, total= 1.0s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.918, total= 1.2s [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=0.5, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.895, total= 1.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.835, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.834, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.886, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.911, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.872, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.843, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.834, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.887, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.922, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.864, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.852, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.838, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.886, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.922, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.859, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.800, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.820, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.883, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.901, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.859, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.797, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.827, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.887, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.906, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.861, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.797, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.828, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.887, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.904, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.860, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.775, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.866, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.881, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.885, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.819, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.780, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.862, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.883, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.820, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.780, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.862, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.883, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.878, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.819, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.807, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.879, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.870, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.878, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.798, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.806, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.868, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.879, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.798, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.806, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.879, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.868, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.879, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=ls, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.798, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.842, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.848, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.843, total= 0.1s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.851, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.858, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.833, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.862, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.842, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.856, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.864, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.840, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.862, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.842, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.856, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=3, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.864, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.757, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.848, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.838, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.836, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.811, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.760, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.848, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.837, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.844, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.815, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.760, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.848, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.837, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.847, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=4, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.815, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.748, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.835, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.829, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.818, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.839, total= 0.2s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.749, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.834, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.836, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.818, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.840, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.747, total= 0.7s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.834, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.836, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.818, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=5, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.836, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.701, total= 0.4s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.807, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.784, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.852, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=50, random_state=10, subsample=1.0, score=0.814, total= 0.3s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.694, total= 0.7s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.807, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.784, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.859, total= 0.5s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=100, random_state=10, subsample=1.0, score=0.812, total= 0.6s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.701, total= 1.0s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.810, total= 0.8s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.784, total= 0.8s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.859, total= 0.7s [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0 [CV] criterion=mse, learning_rate=1, loss=lad, max_depth=6, min_samples_leaf=1, min_samples_split=4, min_weight_fraction_leaf=0.0, n_estimators=150, random_state=10, subsample=1.0, score=0.814, total= 0.8s
[Parallel(n_jobs=1)]: Done 720 out of 720 | elapsed: 4.7min finished
Out[547]:
GridSearchCV(cv=None, error_score=nan,
estimator=GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0,
criterion='friedman_mse',
init=None, learning_rate=0.1,
loss='ls', max_depth=3,
max_features=None,
max_leaf_nodes=None,
min_impurity_decrease=0.0,
min_impurity_split=None,
min_samples_leaf=1,
min_samples_split=2,
min_weight_fraction_leaf=0.0,
n_estimators=100,
n_ite...
iid='deprecated', n_jobs=None,
param_grid={'criterion': ['friedman_mse', 'mse'],
'learning_rate': [0.1, 0.5, 1], 'loss': ['ls', 'lad'],
'max_depth': [3, 4, 5, 6], 'min_samples_leaf': [1],
'min_samples_split': [4],
'min_weight_fraction_leaf': [0.0],
'n_estimators': [50, 100, 150], 'random_state': [10],
'subsample': [1.0]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [548]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'criterion': 'mse', 'learning_rate': 0.1, 'loss': 'ls', 'max_depth': 5, 'min_samples_leaf': 1, 'min_samples_split': 4, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 150, 'random_state': 10, 'subsample': 1.0}
0.9233546065127701
GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='mse', init=None,
learning_rate=0.1, loss='ls', max_depth=5,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=4,
min_weight_fraction_leaf=0.0, n_estimators=150,
n_iter_no_change=None, presort='deprecated',
random_state=10, subsample=1.0, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
In [549]:
gboost = GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='mse', init=None,
learning_rate=0.1, loss='ls', max_depth=5,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=4,
min_weight_fraction_leaf=0.0, n_estimators=150,
n_iter_no_change=None, presort='deprecated',
random_state=10, subsample=1.0, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
In [553]:
gboost.fit(X_train_scaled,y_train)
print("The score on train data: ",gboost.score(X_train_scaled,y_train))
print("\nThe score on test data: ",gboost.score(X_test_scaled,y_test))
The score on train data: 0.9891914133000961 The score on test data: 0.9376440400421949
In [554]:
y_pred = gboost.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# Gradient boosting model has a score of almost 94% and r2 as 0.93% with a RMSE value of '4'.
# This is a good model
The RMSE score is 4.165987760466133 The R-squared value is 0.9287443858422618
In [555]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='mse', init=None,
learning_rate=0.1, loss='ls', max_depth=5,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=4,
min_weight_fraction_leaf=0.0, n_estimators=150,
n_iter_no_change=None, presort='deprecated',
random_state=10, subsample=1.0, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [556]:
model= "Gradient Boosting Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
89.21% to 97.76% 2.58 to 5.63 0.88 to 0.98
In [557]:
h = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'89.21% to 97.76%',
'RMSE':'2.58 to 5.63','R-squared':'0.88 to 0.98'} ,index=[8])
h
Out[557]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 8 | Gradient Boosting Regressor | 89.21% to 97.76% | 2.58 to 5.63 | 0.88 to 0.98 |
RANDOM FOREST REGRESSOR¶
In [585]:
param_grid = {
'n_estimators':[50,100,150],
'criterion':['mse','mae'],
'max_depth':[4,5,6,7,8],
'min_samples_split':[3],
'min_samples_leaf':[1],
'random_state':[seed],
}
In [586]:
grid = GridSearchCV(RandomForestRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 30 candidates, totalling 150 fits [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
[CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.752, total= 0.2s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.767, total= 0.2s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10
[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.3s remaining: 0.0s
[CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.788, total= 0.2s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.805, total= 0.2s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.735, total= 0.2s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.755, total= 0.4s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.766, total= 0.4s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.788, total= 0.3s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.806, total= 0.3s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.736, total= 0.3s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.754, total= 0.6s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.777, total= 0.6s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.788, total= 0.5s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.806, total= 0.5s [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.738, total= 0.4s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.813, total= 0.1s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.830, total= 0.2s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.838, total= 0.2s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.853, total= 0.2s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.803, total= 0.2s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.815, total= 0.3s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.829, total= 0.3s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.838, total= 0.4s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.855, total= 0.4s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.804, total= 0.3s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.817, total= 0.5s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.837, total= 0.5s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.838, total= 0.4s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.854, total= 0.6s [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.807, total= 0.5s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.836, total= 0.2s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.869, total= 0.2s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.863, total= 0.2s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.879, total= 0.2s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.838, total= 0.2s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.839, total= 0.4s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.868, total= 0.3s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.865, total= 0.3s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.881, total= 0.3s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.840, total= 0.3s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.841, total= 0.5s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.873, total= 0.5s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.863, total= 0.6s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.881, total= 0.6s [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.841, total= 0.5s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.852, total= 0.2s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.895, total= 0.2s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.878, total= 0.2s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.890, total= 0.2s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.861, total= 0.2s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.855, total= 0.4s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.894, total= 0.4s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.877, total= 0.4s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.893, total= 0.4s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.863, total= 0.4s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.856, total= 0.6s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.897, total= 0.5s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.876, total= 0.5s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.893, total= 0.6s [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.863, total= 0.6s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.861, total= 0.2s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.908, total= 0.2s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.888, total= 0.2s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.899, total= 0.2s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.873, total= 0.2s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.863, total= 0.4s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.909, total= 0.4s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.886, total= 0.4s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.901, total= 0.4s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.875, total= 0.4s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.864, total= 0.6s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.911, total= 0.5s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.884, total= 0.5s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.900, total= 0.5s [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mse, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.875, total= 0.6s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.749, total= 0.7s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.762, total= 0.7s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.779, total= 0.6s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.802, total= 0.6s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.693, total= 0.6s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.754, total= 1.2s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.766, total= 1.2s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.774, total= 1.2s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.801, total= 1.4s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.701, total= 1.4s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.753, total= 2.3s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.772, total= 2.0s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.776, total= 2.1s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.802, total= 2.5s [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=4, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.701, total= 2.4s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.805, total= 0.9s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.830, total= 0.8s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.833, total= 1.1s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.847, total= 0.9s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.785, total= 0.7s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.807, total= 1.7s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.831, total= 2.2s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.827, total= 1.8s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.844, total= 1.4s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.789, total= 1.6s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.807, total= 2.6s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.837, total= 2.1s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.826, total= 1.9s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.845, total= 2.0s [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=5, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.790, total= 2.1s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.831, total= 0.7s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.868, total= 0.7s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.865, total= 0.8s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.876, total= 0.7s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.825, total= 0.8s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.835, total= 1.4s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.868, total= 1.4s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.861, total= 1.6s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.874, total= 1.8s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.830, total= 2.2s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.836, total= 2.4s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.872, total= 2.8s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.858, total= 2.4s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.874, total= 2.3s [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=6, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.832, total= 2.3s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.848, total= 0.8s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.887, total= 0.8s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.880, total= 1.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.888, total= 0.9s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.844, total= 1.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.849, total= 2.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.888, total= 1.6s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.876, total= 1.6s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.889, total= 1.7s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.852, total= 2.0s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.850, total= 2.5s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.891, total= 2.6s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.875, total= 2.5s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.891, total= 2.5s [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=7, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.852, total= 3.0s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.862, total= 0.9s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.898, total= 0.8s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.889, total= 0.8s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.899, total= 0.8s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=50, random_state=10, score=0.860, total= 0.9s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.863, total= 1.6s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.901, total= 1.7s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.887, total= 1.7s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.898, total= 1.7s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=100, random_state=10, score=0.866, total= 1.7s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.864, total= 2.5s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.904, total= 2.8s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.885, total= 3.2s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.899, total= 3.1s [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10 [CV] criterion=mae, max_depth=8, min_samples_leaf=1, min_samples_split=3, n_estimators=150, random_state=10, score=0.865, total= 3.2s
[Parallel(n_jobs=1)]: Done 150 out of 150 | elapsed: 2.5min finished
Out[586]:
GridSearchCV(cv=None, error_score=nan,
estimator=RandomForestRegressor(bootstrap=True, ccp_alpha=0.0,
criterion='mse', max_depth=None,
max_features='auto',
max_leaf_nodes=None,
max_samples=None,
min_impurity_decrease=0.0,
min_impurity_split=None,
min_samples_leaf=1,
min_samples_split=2,
min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=None,
oob_score=False, random_state=None,
verbose=0, warm_start=False),
iid='deprecated', n_jobs=None,
param_grid={'criterion': ['mse', 'mae'],
'max_depth': [4, 5, 6, 7, 8], 'min_samples_leaf': [1],
'min_samples_split': [3],
'n_estimators': [50, 100, 150], 'random_state': [10]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [587]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'criterion': 'mse', 'max_depth': 8, 'min_samples_leaf': 1, 'min_samples_split': 3, 'n_estimators': 150, 'random_state': 10}
0.8868907232195353
RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',
max_depth=8, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=3, min_weight_fraction_leaf=0.0,
n_estimators=150, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
In [589]:
randf = RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',
max_depth=8, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=3, min_weight_fraction_leaf=0.0,
n_estimators=150, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
In [590]:
randf.fit(X_train_scaled,y_train)
print("The score on train data: ",randf.score(X_train_scaled,y_train))
print("\nThe score on test data: ",randf.score(X_test_scaled,y_test))
The score on train data: 0.9610761923400862 The score on test data: 0.8893289294654667
In [591]:
y_pred = randf.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# random forest has a score of 89% and rmse value of 5 anf r2 as 0.86
The RMSE score is 5.550039325728872 The R-squared value is 0.8636556995079089
In [592]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',
max_depth=8, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=3, min_weight_fraction_leaf=0.0,
n_estimators=150, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [593]:
model= "Random Forest Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
84.58% to 94.95% 3.82 to 6.51 0.81 to 0.94
In [594]:
i = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'84.58% to 94.95%',
'RMSE':'3.82 to 6.51','R-squared':'0.81 to 0.94'} ,index=[9])
i
Out[594]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 9 | Random Forest Regressor | 84.58% to 94.95% | 3.82 to 6.51 | 0.81 to 0.94 |
EXTRA TREES REGRESSOR¶
In [598]:
param_grid={
'n_estimators':[50,100,150],
'criterion':['mse','mae'],
'max_depth':[3,4,5,6,7],
'random_state':[seed],
}
In [599]:
grid = GridSearchCV(ExtraTreesRegressor(), param_grid, refit = True, verbose = 3)
grid.fit(X_train_scaled,y_train)
Fitting 5 folds for each of 30 candidates, totalling 150 fits [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10 ....
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
[CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10, score=0.647, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10, score=0.643, total= 0.1s [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10 ....
[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.1s remaining: 0.0s [Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.2s remaining: 0.0s
[CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10, score=0.638, total= 0.1s [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10, score=0.659, total= 0.1s [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=3, n_estimators=50, random_state=10, score=0.632, total= 0.1s [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10, score=0.650, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10, score=0.648, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10, score=0.635, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10, score=0.656, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=100, random_state=10, score=0.635, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10, score=0.650, total= 0.3s [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10, score=0.650, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10, score=0.634, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10, score=0.654, total= 0.2s [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=3, n_estimators=150, random_state=10, score=0.638, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10, score=0.742, total= 0.1s [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10, score=0.757, total= 0.1s [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10, score=0.746, total= 0.1s [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10, score=0.749, total= 0.1s [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=4, n_estimators=50, random_state=10, score=0.719, total= 0.1s [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10, score=0.730, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10, score=0.756, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10, score=0.740, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10, score=0.751, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=100, random_state=10, score=0.716, total= 0.2s [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10, score=0.729, total= 0.4s [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10, score=0.756, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10, score=0.739, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10, score=0.749, total= 0.3s [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=4, n_estimators=150, random_state=10, score=0.718, total= 0.3s [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10, score=0.787, total= 0.1s [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10, score=0.819, total= 0.1s [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10, score=0.797, total= 0.1s [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10, score=0.814, total= 0.1s [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=5, n_estimators=50, random_state=10, score=0.783, total= 0.1s [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10, score=0.781, total= 0.2s [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10, score=0.817, total= 0.2s [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10, score=0.797, total= 0.2s [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10, score=0.813, total= 0.2s [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=100, random_state=10, score=0.782, total= 0.2s [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10, score=0.776, total= 0.3s [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10, score=0.818, total= 0.3s [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10, score=0.797, total= 0.3s [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10, score=0.815, total= 0.3s [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=5, n_estimators=150, random_state=10, score=0.778, total= 0.3s [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10, score=0.814, total= 0.1s [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10, score=0.854, total= 0.1s [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10, score=0.844, total= 0.1s [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10, score=0.859, total= 0.1s [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=6, n_estimators=50, random_state=10, score=0.818, total= 0.1s [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10, score=0.811, total= 0.2s [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10, score=0.859, total= 0.3s [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10, score=0.840, total= 0.3s [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10, score=0.860, total= 0.3s [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=100, random_state=10, score=0.821, total= 0.3s [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10, score=0.811, total= 0.5s [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10, score=0.859, total= 0.5s [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10, score=0.838, total= 0.4s [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10, score=0.861, total= 0.4s [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=6, n_estimators=150, random_state=10, score=0.819, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10, score=0.841, total= 0.1s [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10, score=0.890, total= 0.1s [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10, score=0.865, total= 0.1s [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10, score=0.883, total= 0.1s [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mse, max_depth=7, n_estimators=50, random_state=10, score=0.855, total= 0.1s [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10, score=0.839, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10, score=0.887, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10, score=0.861, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10, score=0.881, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=100, random_state=10, score=0.854, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10, score=0.841, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10, score=0.888, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10, score=0.862, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10, score=0.884, total= 0.3s [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mse, max_depth=7, n_estimators=150, random_state=10, score=0.855, total= 0.3s [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10, score=0.608, total= 0.5s [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10, score=0.635, total= 0.6s [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10, score=0.626, total= 0.6s [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10, score=0.650, total= 0.6s [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=3, n_estimators=50, random_state=10, score=0.619, total= 0.5s [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10, score=0.622, total= 0.9s [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10, score=0.635, total= 0.9s [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10, score=0.614, total= 0.9s [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10, score=0.655, total= 0.9s [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=100, random_state=10, score=0.621, total= 0.9s [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10, score=0.622, total= 1.3s [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10, score=0.636, total= 1.3s [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10, score=0.604, total= 1.3s [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10, score=0.651, total= 1.3s [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=3, n_estimators=150, random_state=10, score=0.620, total= 1.3s [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10, score=0.697, total= 0.5s [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10, score=0.737, total= 0.5s [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10, score=0.728, total= 0.5s [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10, score=0.764, total= 0.5s [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=4, n_estimators=50, random_state=10, score=0.697, total= 0.5s [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10, score=0.699, total= 1.0s [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10, score=0.738, total= 1.0s [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10, score=0.718, total= 1.2s [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10, score=0.758, total= 1.2s [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=100, random_state=10, score=0.705, total= 1.3s [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10, score=0.699, total= 1.9s [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10, score=0.737, total= 1.7s [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10, score=0.715, total= 1.9s [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10, score=0.754, total= 1.8s [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=4, n_estimators=150, random_state=10, score=0.712, total= 1.9s [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10, score=0.751, total= 0.8s [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10, score=0.792, total= 0.6s [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10, score=0.783, total= 0.6s [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10, score=0.815, total= 0.9s [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=5, n_estimators=50, random_state=10, score=0.763, total= 0.7s [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10, score=0.758, total= 1.3s [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10, score=0.794, total= 1.3s [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10, score=0.783, total= 1.3s [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10, score=0.819, total= 1.2s [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=100, random_state=10, score=0.756, total= 1.3s [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10, score=0.753, total= 2.1s [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10, score=0.795, total= 2.0s [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10, score=0.783, total= 1.7s [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10, score=0.820, total= 1.7s [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=5, n_estimators=150, random_state=10, score=0.762, total= 1.7s [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10, score=0.805, total= 0.6s [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10, score=0.848, total= 0.6s [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10, score=0.825, total= 0.6s [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10, score=0.862, total= 0.6s [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=6, n_estimators=50, random_state=10, score=0.812, total= 0.6s [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10, score=0.807, total= 1.3s [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10, score=0.848, total= 1.3s [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10, score=0.822, total= 1.3s [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10, score=0.862, total= 1.3s [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=100, random_state=10, score=0.814, total= 1.5s [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10, score=0.803, total= 2.3s [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10, score=0.847, total= 2.3s [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10, score=0.824, total= 2.2s [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10, score=0.865, total= 1.8s [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=6, n_estimators=150, random_state=10, score=0.817, total= 1.8s [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10, score=0.832, total= 0.7s [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10, score=0.880, total= 0.7s [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10, score=0.848, total= 0.7s [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10, score=0.890, total= 0.7s [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10 .... [CV] criterion=mae, max_depth=7, n_estimators=50, random_state=10, score=0.836, total= 0.7s [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10, score=0.830, total= 1.4s [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10, score=0.875, total= 1.5s [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10, score=0.851, total= 1.4s [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10, score=0.885, total= 1.4s [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=100, random_state=10, score=0.837, total= 1.5s [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10, score=0.830, total= 2.2s [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10, score=0.878, total= 2.9s [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10, score=0.852, total= 2.4s [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10, score=0.887, total= 2.0s [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10 ... [CV] criterion=mae, max_depth=7, n_estimators=150, random_state=10, score=0.838, total= 1.9s
[Parallel(n_jobs=1)]: Done 150 out of 150 | elapsed: 1.8min finished
Out[599]:
GridSearchCV(cv=None, error_score=nan,
estimator=ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0,
criterion='mse', max_depth=None,
max_features='auto',
max_leaf_nodes=None,
max_samples=None,
min_impurity_decrease=0.0,
min_impurity_split=None,
min_samples_leaf=1,
min_samples_split=2,
min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=None,
oob_score=False, random_state=None,
verbose=0, warm_start=False),
iid='deprecated', n_jobs=None,
param_grid={'criterion': ['mse', 'mae'],
'max_depth': [3, 4, 5, 6, 7],
'n_estimators': [50, 100, 150], 'random_state': [10]},
pre_dispatch='2*n_jobs', refit=True, return_train_score=False,
scoring=None, verbose=3)
In [600]:
print(grid.best_params_)
print(grid.best_score_)
print(grid.best_estimator_)
{'criterion': 'mse', 'max_depth': 7, 'n_estimators': 50, 'random_state': 10}
0.8665813889607181
ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=7, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=50, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
In [601]:
etree = ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=7, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=50, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
In [602]:
etree.fit(X_train_scaled,y_train)
print("The score on train data: ",etree.score(X_train_scaled,y_train))
print("\nThe score on test data: ",etree.score(X_test_scaled,y_test))
The score on train data: 0.922137358791359 The score on test data: 0.8595643330202364
In [603]:
y_pred = randf.predict(X_test_scaled)
print("The RMSE score is ", np.sqrt(mse(y_pred,y_test)))
print("The R-squared value is ",r2_score(y_pred,y_test))
# The extra trees model has a score of 86% with RMSE 5.5 and r2 value as 0.86
The RMSE score is 5.550039325728872 The R-squared value is 0.8636556995079089
In [604]:
scores = []
RMSE = []
r2= []
kf = KFold(n_splits=10, shuffle=False)
for train_index, test_index in kf.split(X,Y):
X_train, X_test, y_train, y_test = X[train_index], X[test_index], Y[train_index], Y[test_index]
ss_kf = StandardScaler()
X_train_scaled = ss_kf.fit_transform(X_train)
X_test_scaled = ss_kf.transform(X_test)
model = ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=7, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=50, n_jobs=None, oob_score=False,
random_state=10, verbose=0, warm_start=False)
model.fit(X_train_scaled, y_train)
y_pred = model.predict(X_test_scaled)
scores.append(model.score(X_test_scaled, y_test))
RMSE.append(np.sqrt(mse(y_pred, y_test)))
r2.append(r2_score(y_pred,y_test))
In [605]:
model= "Extra Tree Regressor"
print("{:.2f}% to {:.2f}%".format((np.mean(scores)-2*np.std(scores))*100,(np.mean(scores)+2*np.std(scores))*100))
print("{:.2f} to {:.2f}".format((np.mean(RMSE)-2*np.std(RMSE)),(np.mean(RMSE)+2*np.std(RMSE))))
print("{:.2f} to {:.2f}".format((np.mean(r2)-2*np.std(r2)),(np.mean(r2)+2*np.std(r2))))
81.00% to 92.62% 4.53 to 7.21 0.73 to 0.90
In [607]:
j = pd.DataFrame({'Model perfomance at 95% confidence': model,'Score':'81.00% to 92.62%',
'RMSE':'4.53 to 7.21','R-squared':'0.73 to 0.90'} ,index=[10])
j
Out[607]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 10 | Extra Tree Regressor | 81.00% to 92.62% | 4.53 to 7.21 | 0.73 to 0.90 |
In [609]:
final_model = pd.concat([a,b,c,d,e,f,g,h,i,j])
CONCLUSION¶
In [ ]:
# The model was first analysed. There were no NAN values. However, there were many '0' values. (almost 600 or more entries)
# But these '0' here does not mean it is a null entry. It maybe because of the fact that,those attributes were not added for that particular concrete composition
# univaritate analysis and bivariate analysis were performed. The 75 percentile value and max value were far apart.
# Also, from the boxplot, it was inferred that there are presence of outliers.
# These outliers were treated by the principle of removing values which are:
# 1) less than 1.5 times the IQR, from the First quartile
# 2) greater than 1.5 times the IQR, from the third quartile
# Pairplot and heatmap analysis showed that there was no attribute that was in good correlation with the target attribute.
# Only cement was of the highest correlation (50%)
# A composite feature was formed, which was a combination of coarge_agg and fine_agg --> coarse_agg /- kg of fine_agg
# Next, cluster analysis was performed.
# Using Kmeans, 8 clusteres were formed and were analysed cluster wise. However, the clusters were highly overlapping
# There was not a single attribute with seperate clusters. Hence the inference from the clusters was very less.
# Despite that, there were one or two clusters in a few attributes, which were acting as a good predictor of that attribute
# for eg: cement vs strength, water vs strength, coarse_agg_perkgof_fin_agge vs strength
# Next feature importance was obtained from linear regression model and decision tree.
# It was inferred that, coarse_agg_fine_agg, superplastic and ash were of least importance
Model Perfomance
In [610]:
final_model
Out[610]:
| Model perfomance at 95% confidence | Score | RMSE | R-squared | |
|---|---|---|---|---|
| 1 | Linear Regression | 64.96% to 85.91% | 6.45 to 9.57 | 0.54 to 0.82 |
| 2 | Ridge Regression | 64.99% to 85.88% | 6.45 to 9.57 | 0.53 to 0.82 |
| 3 | Lasso Regression | 65.22% to 85.70% | 6.44 to 9.58 | 0.52 to 0.81 |
| 4 | Decision Tree Regressor | 77.62% to 92.39% | 5.20 to 7.26 | 0.76 to 0.91 |
| 5 | Support Vector Regressor | 84.35% to 95.53% | 3.59 to 6.65 | 0.83 to 0.95 |
| 6 | KNN Regressor | 80.66% to 89.07% | 4.91 to 7.76 | 0.73 to 0.88 |
| 7 | Ada Boost Regressor | 86.40% to 95.06% | 3.44 to 6.43 | 0.84 to 0.95 |
| 8 | Gradient Boosting Regressor | 89.21% to 97.76% | 2.58 to 5.63 | 0.88 to 0.98 |
| 9 | Random Forest Regressor | 84.58% to 94.95% | 3.82 to 6.51 | 0.81 to 0.94 |
| 10 | Extra Tree Regressor | 81.00% to 92.62% | 4.53 to 7.21 | 0.73 to 0.90 |
In [ ]:
# At 95% confidence level, the simple linear model, ridge and lasso all performed at the same level between:
# 1) 64.9% to 85% for score
# 2) 6.45 to 9.5 for RMSE
# 3) 0.5 to 0.8 for the R-squared
# At 95% confidence level, this is not a "very good model"
# Desicion Tree regressor:
# Decision tree regressor performed better than the linear models in terms of score, RMSE and r-squared.
# But still, it wasn't good enough
# SVR:
# it has a very good score range of 84-95% and RMSE was 4-6.5 and r2 as .83-.95
# This is a good model
# KNN regressor:
# With RMSE between 4.9 to 7.7 and r2 of 0.73-0.88, KNN regressor was performing lesser than the SVR model
# Adaboost:
# Has a score range of 86 to 95% ; RMSE between 3.4 to 6.4 and r2 of 0.84 to 0.95
# This is a very good range interms of RMSE and r2 value
# Gradient boosting:
# With a score range of approximately 90% to 97% and r2 of 0.88 to 0.98, and RMSE of 2.58 to 5.63,
# Gradient boosting is a very good model among the lot
# Random forest regressor:
# has a score of 84-95% and RMSE of 3.82 to 6.51 and r2 of 0.81 to 0.94. This is a good model too
# Extra trees regressor:
# Suprisingly, extra tree regressor also performed well with a score range of 81 to 92 % with RMSE of 4.5 to 7.2
# and r2 of 0.73-0.90
# Among all the models, SVR, ada boost, gradient boost, Random forest and extra tree regressor were the better performing models.
# However, gradient boosting regressor was the "BEST" performing model of the lot, with a score range of 89-98%,
# and with a low RMSE and a r2 value close to 1 (0.88 to 0.98)
# Hence, my final conclusion is,
# At 95% confidence gradient descent predicts the compressive strength of the concrete with :
# 1) score range : 89.21% to 97.76%
# 2) RMSe range : 2.58 to 5.63
# 3) R-squared range : 0.88 to 0.98